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Conferences, Lectures, & Seminars
Events for October
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Seminars in Biomedical Engineering
Mon, Oct 01, 2018 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: B. Hyle Park, PhD, UC-Riverside, Associate Professor of Bioengineering
Talk Title: Novel OCT Imaging
Host: Qifa Zhou
Location: Olin Hall of Engineering (OHE) - 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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Fall 2018 Joint CSC USC/CommNetS-MHI Seminar Series
Mon, Oct 01, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Vanessa Jonsson, City of Hope Beckman Research Institute
Talk Title: Adaptive Clinical Trial Design to Address Acquired Resistance and Therapeutic Failure
Abstract: One of the challenges facing immunotherapy as a durable therapeutic approach in a variety of metastatic cancers is the development of acquired resistance and subsequent therapeutic failure. Widespread clinical applicability of immunotherapy to solid tumors depends on the understanding of response and resistance mechanisms that are mediated by evolving interactions between the immune system and cancer cells. These dynamic interactions are increasingly being identified through longitudinal molecular analysis and immunological profiling and combine to produce an evolving measure of a patient cancer-immune status. However, cancer immune dynamics have yet to be formally quantified and studied as an evolutionary process in the context of immunotherapy clinical trials. To address this, we propose a method to integrate high dimensional, heterogeneous, longitudinal patient-derived cancer and immunological clinical data sets to identify cancer immune dynamics as well as a control theoretic method to preemptively address the onset of resistance through the prediction and synthesis of actionable immunotherapy combination strategies. We apply these methods to genomic and immunological data collected from a patient with recurrent multifocal glioblastoma that elicited a complete response and eventually recurred while enrolled in City of Hope's ongoing IL13R 2-targeting chimeric antigen (CAR) T cell trial for patients with recurrent glioblastoma. We show that dynamic treatment strategies are necessary for the control of tumors with high antigen heterogeneity and propose this as a framework by which to assess the effectiveness of adaptive clinical trial design and patient stratification for combination immunotherapy trials.
Biography: Vanessa Jonsson is an assistant research professor in the and Department of Hematology and Hematopoietic Cell Transplantation and leader of the Computational Immuno-Oncology group in the T Cell Immunotherapy Program at City of Hope. Her research program in computational biology focusses on the integration, mathematical modeling and analysis of large-scale, longitudinal genomic, transcriptomic and immunological data from clinical studies to inform and address the mechanisms of immune-resistant cancer progression. In 2015, Vanessa completed her PhD at Caltech, where she was advised by Richard Murray and David Baltimore. She is a principal investigator on a Parker Institute for Cancer Immunotherapy award to model the evolution of cancer immunity during immunotherapy trials and co-investigator on a California Institute of Regenerative Medicine (CIRM) award to study response and resistance in a phase I CAR T cell trial targeting malignant glioma. She is the recipient of the NIH and NCI career development award in clinical oncology (K12), with a focus on immuno-oncology.
Host: Mihailo Jovanovic
More Info: http://csc.usc.edu/seminars/2018Fall/jonsson.html
More Information: 18.10.01_Vanessa Jonsson CSCUSC Seminar.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Brienne Moore
Event Link: http://csc.usc.edu/seminars/2018Fall/jonsson.html
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Six Sigma Green Belt for Process Improvement
Tue, Oct 02, 2018
Executive Education
Conferences, Lectures, & Seminars
Talk Title: Six Sigma Green Belt for Process Improvement
Abstract: Abstract: Learn how to integrate principles of business, statistics, and engineering to achieve tangible results. Master the use of Six Sigma to quantify the critical quality issues in your company. Once the issues have been quantified, statistics can be applied to provide probabilities of success and failure. Six Sigma methods increase productivity and enhance quality.
Host: USC Viterbi Executive Education
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-green-belt-process-improvement/
Audiences: Registered Attendees
Contact: Viterbi Professional Programs
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PhD Defense
Tue, Oct 02, 2018 @ 01:00 PM - 03:00 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Yuan Jin , Mork Family Department of Chemical Engineering
Talk Title: Statistical modeling and process data analytics for smart manufacturing
Abstract: Smart manufacturing has been the focus of many researchers and has been extended to varies areas. With the increased complexity of the manufacturing process and the variety data collected from various aspects throughout the process, process data analytics is thus essential to discover process knowledge and predict the future production. In this dissertation, we introduced two challenges accompanied by smart manufacturing and discussed how we handle the challenges for processes with different manufacturing characters. The two challenges are "complexity" and "variety", the areas of applications are additive manufacturing (AM) and pharmaceutical manufacturing.
To handle the challenges accompanying with AM, we first study a statistical modeling and optimal compensation approach to predict and improve the shape accuracy of AM printed parts, especially for the out-of-plane deviation. This method is data driven and thus, not blocked by the complicated AM physical mechanism. Moreover, this method is able to deal with low volume sample data and high volume geometric variety. The feasibility and effectiveness of this approach is proved by experimental study.
To deal with the challenges accompanying with pharmaceutical manufacturing, we proposed a two-stage strategy to study a large-scale cell culture manufacturing process variability. This strategy not only adopts multivariate analysis (MVA) and machine learning (ML) methods on intricate multiple-step bio-processes, but also takes use of multilevel heterogeneous datasets to unveil hidden process characteristics and provide insights into factors affecting process quality. This strategy has been applied to a real antibody pharmaceutical manufacturing, pointing to new cues for domain experts to better understand the process.
Biography: Yuan Jin is a Ph.D. candidate in Mork Family Department of Chemical Engineering & Materials Science at University of Southern California (USC), Los Angeles, CA. She received her B.E. degree in Electrical Engineering from Zhejiang University, Hangzhou, Zhejiang in 2013. Her research is about statistical modeling and process data analytics for smart manufacturing.
Host: Dr. Joe Qin
Location: Hedco Pertroleum and Chemical Engineering Building (HED) - 116
Audiences: Everyone Is Invited
Contact: Karen Woo/Mork Family
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Epstein Institute Seminar - ISE 651
Tue, Oct 02, 2018 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Ying Cui, Postdoctoral Scholar - Research Associate, USC, Daniel J. Epstein Department of Industrial and Systems Engineering
Talk Title: Composite Difference-Max Programs for Modern Statistical Estimations
Host: Professor Jong-Shi Pang
More Information: October 2, 2018.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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Mork Family Department of Chemical Engineering and Materials Science Seminar - Lyman L. Handy Colloquia
Tue, Oct 02, 2018 @ 04:00 PM - 05:20 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Dr. Doraiswami Ramkrishna , H.C.Peffer Distinguished Professor, Davidson School of Chemical Engineering. Purdue University
Talk Title: Metabolic Complexity. Is there Music Behind it?
Abstract: The complexity of metabolic networks would appear to fit in more appropriately with a cacophonic scenario than anything remotely musical. However, this talk will attempt to show that a mathematical view can be had of this complex process in which the phenomenon of metabolic regulation can be likened to the conductor of a symphonic orchestra summoning combinations of instruments representing metabolic reactions towards superlative music. It will be the objective of this seminar to let this analogy lead the discussion of a cybernetic theory of cellular metabolism which interprets the diversity of gene expression as a targeted effort to maximize the organism's survival. The applicability of the model to bioprocess engineering is demonstrated.
Host: Professor Theo Tsotsis
Location: John Stauffer Science Lecture Hall (SLH) - 200
Audiences: Everyone Is Invited
Contact: Karen Woo/Mork Family
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Six Sigma Green Belt for Process Improvement
Wed, Oct 03, 2018
Executive Education
Conferences, Lectures, & Seminars
Talk Title: Six Sigma Green Belt for Process Improvement
Abstract: Abstract: Learn how to integrate principles of business, statistics, and engineering to achieve tangible results. Master the use of Six Sigma to quantify the critical quality issues in your company. Once the issues have been quantified, statistics can be applied to provide probabilities of success and failure. Six Sigma methods increase productivity and enhance quality
Host: USC Viterbi Executive Education
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-green-belt-process-improvement/
Audiences: Registered Attendees
Contact: Viterbi Professional Programs
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SERC Talks
Wed, Oct 03, 2018 @ 10:00 AM - 11:00 AM
Systems Architecting and Engineering, USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Bill Curtis, Senior VP and Chief Scientist, CAST Software; Head of CAST Research Labs; Executive Director, Consortium for IT Software Quality (CISQ)
Talk Title: How Can We Advance Structural Quality Analysis with Standards and Machine Learning?
Series: Systems and Software Qualities Tradespace Analysis
Abstract: The C-suite is fed up with software disasters putting the quarterly statement at risk as they digitize the business. They will demand more accountability and force improvements in software processes that may clash with agile culture. Business critical applications have become so complex and demand for functionality so immediate that human-based quality practices are no longer sufficient. Developer capabilities must be enhanced by system-level analysis of structural weaknesses and operational risks enabled by structural quality technology and measurement standards supported in DevOps toolchains. Empirical results will be reported from research on how some of the most severe Security and Reliability flaws are distributed in business applications. Recent results from machine learning research in structural quality will be discussed along with some caveats about what to expect. International standards for measuring the structural quality of software developed by the Consortium for IT Software Quality (CISQ) that supplement ISO 25023 will be reviewed. The talk concludes with organizational requirements for successfully adopting these advances.
This talk is broadcast on WebEx. Visit the registration link at the event link to join the broadcast. Alternatively, join using
Event number: 667 578 255
Registration ID: 543308
Event password: SERC
Biography: Dr. Bill Curtis is the Executive Director of the Consortium for IT Software Quality (CISQ), an industry consortium chartered with building international standards for automating the measurement of size and structural quality from source code. He is also Senior Vice President and Chief Scientist at CAST Software, where he heads CAST Research Labs. He led development of the Capability Maturity Model (CMM) while at the Software Engineering Institute. He has worked at the University of Washington, GE Space Division, the ITT Programming Technology Center, Microelectronics and Computer Technology Corporation (MCC), the SEI, TeraQuest Metrics which he co-founded, Borland Software Company, and CAST. He has published 4 books, over 150 papers, and is an IEEE Fellow for his contributions to software process improvement and measurement.
Host: Prof. Barry Boehm
More Info: https://sercuarc.org/event/serc-talks-how-can-we-advance-structural-quality-analysis-with-standards-and-machine-learning/
Webcast: https://sercuarc.org/event/serc-talks-how-can-we-advance-structural-quality-analysis-with-standards-and-machine-learning/Location: This talk is broadcast on WebEx.
WebCast Link: https://sercuarc.org/event/serc-talks-how-can-we-advance-structural-quality-analysis-with-standards-and-machine-learning/
Audiences: Everyone Is Invited
Contact: Ms. Mimi Marcus
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CS Colloquium: Ardalan Amiri Sani (UC Irvine) - Dealing with Vulnerabilities in Device Drivers
Wed, Oct 03, 2018 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Ardalan Amiri Sani, UC Irvine
Talk Title: Dealing with Vulnerabilities in Device Drivers
Series: Computer Science Colloquium
Abstract: Vulnerabilities in the device drivers of today's commodity operating systems (e.g., Android) remain a security concern due to the monolithic structure of the kernel. In this talk, we investigate three methods to mitigate this concern, with a focus on mobile devices. These approaches include a novel tool to find and fix these vulnerabilities, an efficient vetting layer to make exploits harder, and a device driver design possible for I/O devices with virtualization support.
This lecture satisfies requirements for CSCI 591: Research Colloquium. Please note, due to limited capacity, seats will be first come first serve.
Biography: Ardalan Amiri Sani is an Assistant Professor in the Computer Science department at UC Irvine. His research is at the intersection of mobile computing, security, and operating systems. His work has appeared in various top-tier conferences such as MobiSys (including a best paper award), USENIX Security, CCS, and ASPLOS. Ardalan received his Ph.D. from Rice University in 2015.
Host: Ramesh Govindan
Location: Olin Hall of Engineering (OHE) - 100D
Audiences: Everyone Is Invited
Contact: Computer Science Department
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On the Role of Interaction in Future Mobility Systems, from Vehicle-Centric to System-Wide Control
Wed, Oct 03, 2018 @ 12:00 PM - 01:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Marco Pavone, Aeronautics & Astronautics, Stanford University
Talk Title: On the Role of Interaction in Future Mobility Systems, from Vehicle-Centric to System-Wide Control
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: In this talk I will discuss my work on self-driving vehicles, with an emphasis on accounting for interactions with external counterparts at both the vehicle- and system-levels. Specifically, I will first discuss a decision-making framework that enables a self-driving vehicle to proactively interact with humans to infer their intents, and to use such information for safe and efficient driving. I will then turn the discussion to the operational and economic aspects of autonomous mobility-on-demand (AMoD) systems, with an emphasis on the interaction between AMoD and other infrastructures, such as the electric power and public transit networks.
Biography: Dr. Marco Pavone is an Assistant Professor of Aeronautics and Astronautics at Stanford University, where he is the Director of the Autonomous Systems Laboratory and Co-Director of the Center for Automotive Research at Stanford. Before joining Stanford, he was a Research Technologist within the Robotics Section at the NASA Jet Propulsion Laboratory. He received a Ph.D. degree in Aeronautics and Astronautics from the Massachusetts Institute of Technology in 2010. His main research interests are in the development of methodologies for the analysis, design, and control of autonomous systems, with an emphasis on self-driving cars, autonomous aerospace vehicles, and future mobility systems. He is a recipient of a Presidential Early Career Award for Scientists and Engineers, an ONR YIP Award, an NSF CAREER Award, a NASA Early Career Faculty Award, a Hellman Faculty Scholar Award, and was named NASA NIAC Fellow in 2011. He was identified by the American Society for Engineering Education (ASEE) as one of America's 20 most highly promising investigators under the age of 40. His work has been recognized with best paper nominations or awards at the Field and Service Robotics Conference, at the Robotics: Science and Systems Conference, and at NASA symposia. He is currently serving as an Associate Editor for the IEEE Control Systems Magazine.
Host: Professor Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
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Six Sigma Green Belt for Process Improvement
Thu, Oct 04, 2018
Executive Education
Conferences, Lectures, & Seminars
Talk Title: Six Sigma Green Belt for Process Improvement
Abstract: Abstract: Learn how to integrate principles of business, statistics, and engineering to achieve tangible results. Master the use of Six Sigma to quantify the critical quality issues in your company. Once the issues have been quantified, statistics can be applied to provide probabilities of success and failure. Six Sigma methods increase productivity and enhance quality.
Host: USC Viterbi Executive Education
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-green-belt-process-improvement/
Audiences: Registered Attendees
Contact: Viterbi Professional Programs
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CS Colloquium: Mohammad Soleymani (USC-ICT) - What Do Machines Learn in Emotion Recognition from EEG Signals?
Thu, Oct 04, 2018 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Mohammed Soleymani, USC-ICT
Talk Title: What Do Machines Learn in Emotion Recognition from EEG Signals?
Series: CS Colloquium
Abstract: Machines that are able to read our emotions and cognitive states make better companions. Emotions are often sensed by their external manifestations such as facial and vocal expressions. Additionally, studies in affective neuroscience have identified a set of emotional neural activities that can be captured by eletroencephalogram (EEG) signals, including asymmetric frontal brain activity and increase in information transfer. Motivated by these findings, a growing number of studies report developing EEG-based emotion recognition systems with promising results. In this talk, I first present my work on recognizing emotions of people watching videos. I then present a follow up study in which we aimed to better understand what machine learns in such scenarios. In the follow up work, we recorded a dataset which includes spontaneous emotions and posed expressions. Our analysis on the data collected in the follow up study demonstrates that the performance of existing EEG-based emotion recognition methods significantly decreases when evaluated across different corpora. We also found that models trained on spontaneous emotions perform well on recognizing mimicked expressions. Our results provide evidence that stimuli-related sensory information and facial electromyogram activities are the main components learned by machine learning models for emotion recognition using EEG signals.
This lecture satisfies requirements for CSCI 591: Research Colloquium. Please note, due to limited capacity, seats will be first come first serve.
Biography: Mohammed Soleymani is a research scientist with the USC Institute of Creative Technologies. He received his PhD in computer science from the University of Geneva in 2011. From 2012 to 2014, he was a Marie Curie fellow at Imperial College London. Prior to joining ICT, he was a research scientist at the Swiss Center for Affective Sciences, University of Geneva. His main line of research involves developing automatic emotion recognition and behavior understanding methods using physiological signals and facial expressions. He is also interested in understanding subjective attributes in multimedia content, e.g, predicting whether an image is interesting from its pixels or automatic recognition of music mood from acoustic content. He is a recipient of the Swiss National Science Foundation Ambizione grant and the EU Marie Curie fellowship. He has served on multiple conference organization committees and editorial roles, most notably as associate editor for the IEEE Transactions on Affective Computing and technical program chair for ACM ICMI 2018 and ACII 2017. He is one of the founding organizers of the MediaEval multimedia retrieval benchmarking campaign and the president elect for the Association for Advancement of Affective Computing (AAAC).
Host: David Traum
Location: Ronald Tutor Hall of Engineering (RTH) - 115
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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NL Seminar- CoQA, A Conversational Question Answering Challenge
Thu, Oct 04, 2018 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Siva Reddy , Stanford University
Talk Title: CoQA: A Conversational Question Answering Challenge
Series: Natural Language Seminar
Abstract: Humans gather information by engaging in conversations involving a series of interconnected questions and answers. For machines to assist in information gathering, it is therefore essential to enable them to answer conversational questions. In this talk, I will present our work on CoQA, a novel dataset for building Conversational Question Answering systems. CoQA contains 127k questions with answers, obtained from 8k conversations about text passages from seven diverse domains. The questions are conversational, and the answers are free-form text with their corresponding evidence highlighted in the passage. We analyze CoQA in depth and show that conversational questions have challenging phenomena not present in existing reading comprehension datasets, e.g., coreference and pragmatic reasoning. We evaluate strong conversational and reading comprehension models on CoQA. The best system obtains an F1 score of 65.1%, which is 23.7 points behind human performance 88.8 percent, indicating there is ample room for improvement. We launch CoQA as a challenge to the community. See link below.
Biography: Siva Reddy is a postdoc in Computer Science at Stanford University working with Prof. Christopher Manning. His research focuses on enabling natural communication between humans and machines. Prior to the postdoc, he was a Google PhD Fellow at the University of Edinburgh under the supervision of Prof. Mirella Lapata and Prof. Mark Steedman.
Host: Xusen Yin
More Info: https://stanfordnlp.github.io/coqa/
Webcast: https://bluejeans.com/s/iHu_F/Location: Information Science Institute (ISI) - 6th Floor Conf Rm-CR# 689
WebCast Link: https://bluejeans.com/s/iHu_F/
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: https://stanfordnlp.github.io/coqa/
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CENG Seminar Series
Thu, Oct 04, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Yu Hua, Huazhong University of Science and Technology
Talk Title: Encrypted Non-volatile Main Memory Systems
Abstract: Non-volatile memory (NVM) technologies are considered as promising candidates of the next-generation main memory. However, the non-volatility of NVMs leads to new security vulnerabilities. Memory encryption can be employed to mitigate the security vulnerabilities, but it increases the number of bits written to NVMs due to the diffusion property and thereby aggravates the NVM wear-out induced by writes. To address these security and endurance challenges, we propose DeWrite, a secure and deduplication-aware scheme to enhance the performance and endurance of encrypted NVMs based on a new in-line deduplication technique and the synergistic integrations of deduplication and memory encryption. Specifically, it performs low-latency in-line deduplication to exploit the abundant cache-line-level duplications leveraging the intrinsic read/write asymmetry of NVMs and light-weight hashing. It also opportunistically parallelizes the operations of deduplication and encryption and allows them to co-locate the metadata for high efficiency. DeWrite was implemented on the gem5 with NVMain.
Biography: Dr. Yu Hua is a professor in Huazhong University of Science and Technology. He was Postdoc Research Associate in McGill University in 2009, and Postdoc Research Fellow in University of Nebraska-Lincoln in 2010-2011. He obtained his B.E and Ph.D degrees from Wuhan University respectively in 2001 and 2005. His research interests include file systems, cloud storage systems, non-volatile memory, big data analytics, etc. He publishes multiple papers in conferences and journals, including OSDI, MICRO, FAST, USENIX ATC, ACM SoCC, SC, HPDC, etc. He serves for multiple international conferences, including USENIX ATC, ASPLOS (ERC), SC, ACM SoCC, RTSS, ICDCS, ICCD, INFOCOM, IPDPS, etc. He is the distinguished member of CCF, senior member of ACM and IEEE, and the member of USENIX. He has been appointed as the Distinguished Speaker of ACM and CCF. His homepage is at: https://csyhua.github.io
Host: Xuehai Qian, xuehai.qian@usc.edu
More Information: 18.10.04_Yu Hua_CENG Seminar.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Brienne Moore
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CS Tech Talk: Parisa Mansourifard (Facebook) - Infrastructure Data Science Team at Facebook
Thu, Oct 04, 2018 @ 03:30 PM - 04:50 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Parisa Mansourifard, Facebook
Talk Title: Infrastructure Data Science Team at Facebook
Series: Computer Science Colloquium
Abstract: In this talk, I will present what my team does at Facebook and what problems we aim to solve. Infrastructure Data Science partners with engineering teams to develop data-driven solutions for significant infrastructure challenges such as app and site performance, systems efficiency and reliability, resource allocation and long-term capacity forecasts. Infra Data Scientists use a range of tools, from A/B testing to machine learning, to help Facebook make decisions about operations and system design. The team contributes to all parts of a project's lifecycle, including scoping, data discovery, research, methodological design, code implementation, and reporting and interpreting final results. The teams' work varies, in line with the complex and diverse challenges of maintaining one of the largest and most advanced enterprise infrastructures in the world. We look for candidates with a wide range of backgrounds to join our team and help with this work.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Parisa Mansourifard is currently a data scientist at Infrastructure data science team at Facebook. Before joining Facebook, she was a data scientist at SupplyFrame Inc. and a part-time lecturer at CS department of University of Southern California teaching machine learning. She received the B.S. and M.S. in electrical engineering from Sharif university of technology, Tehran, Iran, in 2008 and 2010 respectively. She also got a M.S. in computer science and Ph.D. in electrical engineering from University of Southern California, Los Angeles, CA, USA, in 2015 and 2017, respectively. During her Ph.D. she held Viterbi Dean fellowships in 2011-2014 and AAUW dissertation completion fellowship in 2015-2016. She also got a best paper award for the operations research track at EU IEOM conference in Paris 2018.
Host: Computer Science Department
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Computer Science Department
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Farewell to Servers: Hardware, Software, and Network Approaches towards Datacenter Resource Disaggregation
Fri, Oct 05, 2018 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Yiying Zhang, Purdue University
Talk Title: Farewell to Servers: Hardware, Software, and Network Approaches towards Datacenter Resource Disaggregation
Abstract: Datacenters have been using a "monolithic" server model for decades, where each server has a motherboard that hosts a set of hardware devices such as processors and memory chips. This monolithic architecture is easy to deploy but cannot fully support the growing hardware heterogeneity in datacenters or provide hardware elasticity, failure isolation, and efficient resource utilization. Going forward, we have to rethink the decade-long server-centric model.
Our answer is to break the monolithic server model into distributed, network-attached hardware components that can each manage its own resources and can fail independently. For the past three years, my lab has been working on such datacenter "resource disaggregation" at system software, networking, and hardware levels. In this talk, I will discuss our various efforts in building a disaggregated datacenter (or "DC-3.0"). Specifically, I will focus on two systems: LegoOS, a new distributed, disseminated OS designed for datacenter resource disaggregation (OSDI'18), and LITE, a Local Indirection TiEr in kernel to virtualize native RDMA into a flexible, high-level, easy-to-use abstraction (SOSP'17).
Biography: Yiying Zhang is an assistant professor in the School of Electrical and Computer Engineering at Purdue University. Her research interests span operating systems, distributed systems, datacenter networking, and computer architecture, with a focus on building software, hardware, network systems for next-generation datacenters. Her lab is pioneering in the field of datacenter resource disaggregation and is among the few groups in the world that builds new OSes and full-stack, cross-layer systems. She has published at and served on the program committees of top systems conferences such as SOSP, OSDI, and ASPLOS, and her work has attracted various industry and academia attentions. Yiying received her Ph.D. from the Department of Computer Sciences at the University of Wisconsin-Madison and worked as a postdoctoral scholar at the University of California, San Diego before joining Purdue.
Host: Xuehai Qian, xuehai.qian@usc.edu
More Information: 18.10.05_Yiying Zhang .pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Brienne Moore
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W.V.T. RUSCH ENGINEERING HONORS COLLOQUIUM
Fri, Oct 05, 2018 @ 01:00 PM - 01:50 PM
Viterbi School of Engineering Student Affairs
Conferences, Lectures, & Seminars
Speaker: Jim Cahill , Developer of Mindfulness-Based Biofeedback Training, Medicine Mind, Inc., Silvergate Medical Center
Talk Title: Contemplative Science: Empirical Approaches to Understanding the Mind
Host: EHP and Dr. Prata
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Amanda McCraven
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BME seminars
Fri, Oct 05, 2018 @ 02:00 PM - 04:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Steve Kay, PhD, USC Keck School of Medicine, Provost Professor of Neurology, Biomedical Engineering and Biological Sciences, Director of Convergent Bioscience
Talk Title: Circadian Gene Regulatory Networks in Health and Disease
Series: Seminars in BME (Lab Rotations)
Host: Brent Liu, PhD
Location: Corwin D. Denney Research Center (DRB) - 145a
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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Astani Civil and Environmental Engineering Seminar
Fri, Oct 05, 2018 @ 03:00 PM - 04:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. David Cwiertny, University of Iowa
Talk Title: Beyond emerging contaminants: bioactive transformation products and what we should do about them
Abstract: See Attachment
Host: Dr. Daniel McCurry
More Information: Cwiertny_Announcement.pdf
Location: Ray R. Irani Hall (RRI) - 101
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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Niels Reimers - Keynote Seminar on Entrepreneurship & Innovation, Laboratory to Market: University Technology Licensing, Monday, October 8th at 10:30am in EEB 132
Mon, Oct 08, 2018 @ 10:30 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Niels Reimers, Niels Reimers
Talk Title: Laboratory to Market: University Technology Licensing
Abstract: Abstract: A discussion of today's knowledge society, role of universities, specifics of Stanford's experience, cultural and other impediments to innovation, university policies, and elements of a university technology licensing office.
Biography: Biography: Niels Founded and directed Stanford Office of Technology Licensing, 1968-91. During the 22 years he managed the program at Stanford, he was loaned to Massachusetts Institute of Technology to reform its program, and to the University of California, Berkeley to found its program.
Cumulative licensing income to Stanford from an outside management firm, from 1954-67, totaled about $4,500. Niels proposed a pilot year-long licensing office with a marketing focus, which pilot year (1968-69) achieved $55,000 in licensing income. A permanent office then was approved, with a staff of Niels and a secretary/office manager. As the work load grew from increasing numbers of technology disclosures from faculty and students, staff were added. Cumulative licensing income from 1968 is expected to top $2 billion in fiscal year 2019.
Host: Ming Hsieh Institute
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Seminars in Biomedical Engineering
Mon, Oct 08, 2018 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Hongqiao Zhang, MD, PhD, USC, Research Assistant Professor of Gerontology
Talk Title: Nano particle effect on health
Host: Qifa Zhou
Location: Olin Hall of Engineering (OHE) - 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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Fall 2018 Joint CSC@USC/CommNetS-MHI Seminar Series
Mon, Oct 08, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Murat Arcak, University of California Berkeley
Talk Title: Scalable Symbolic Control
Abstract: Finite abstractions of continuous dynamical systems play a central role in synthesizing controllers that enforce complex specifications, such as those expressed in temporal logic, and enable the designer to leverage tools from model checking and reactive synthesis. The resulting controller is symbolic, meaning that it only requires knowledge of quantized states that represent the currently occupied partition of the state space. Existing computational tools for this approach have been limited to small systems because both the abstraction and synthesis steps suffer from severe time and space bottlenecks as the system dimension grows. This talk will present recent results that overcome these bottlenecks by exploiting structural system properties. These results include: (1) taking advantage of monotonicity properties of the dynamical model for efficient reachability computations, (2) using sparsity structures in the dependency graph of state variables for parsimonious abstraction algorithms that dramatically reduce runtime, and (3) dividing the control synthesis task into sub-problems of manageable size with compositional procedures. The results will be illustrated with several practically motivated examples.
Biography: Murat Arcak is a professor at UC Berkeley with appointments in the Department of Electrical Engineering and Computer Sciences and Department of Mechanical Engineering. He received the B.S. degree in Electrical Engineering from the Bogazici University, Istanbul (1996) and the M.S. and Ph.D. degrees from the University of California, Santa Barbara (1997 and 2000). His research is in dynamical systems and control theory with applications to synthetic biology, multi-agent systems, and transportation. He received a CAREER Award from the National Science Foundation in 2003, the Donald P. Eckman Award from the American Automatic Control Council in 2006, the Control and Systems Theory Prize from the Society for Industrial and Applied Mathematics (SIAM) in 2007, and the Antonio Ruberti Young Researcher Prize from the IEEE Control Systems Society in 2014. He is a member of SIAM and a fellow of IEEE.
Host: Ketan Savla, ksavla@usc.edu
More Info: http://csc.usc.edu/seminars/2018Fall/arcak.html
More Information: 18.10.08_Murat Arcak CSCUSC Seminar.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Brienne Moore
Event Link: http://csc.usc.edu/seminars/2018Fall/arcak.html
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CS Colloquium: Xinyu Xing (Pennsylvania State University) - Tracking down Software Vulnerabilities from Unexpected Crashes
Tue, Oct 09, 2018 @ 03:40 PM - 04:50 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Xinyu Xing, Pennsylvania State University
Talk Title: Tracking down Software Vulnerabilities from Unexpected Crashes
Series: Computer Science Colloquium
Abstract: Despite the best efforts of developers, software inevitably contains flaws that may be leveraged as security vulnerabilities. Modern operating systems integrate various security mechanisms to prevent software faults from being exploited. To bypass these defenses and hijack program execution, an attacker therefore needs to constantly mutate an exploit and make many attempts. While in their attempts, the exploit triggers a security vulnerability and makes the running process terminate abnormally.
After a program has crashed and terminated abnormally, it typically leaves behind a snapshot of its crashing state in the form of a core dump. While a core dump carries a large amount of information, which has long been used for software debugging, it barely serves as informative debugging aids in locating software faults, particularly memory corruption vulnerabilities. As such, previous research mainly seeks fully reproducible execution tracing to identify software vulnerabilities in crashes. However, such techniques are usually impractical for complex programs. Even for simple programs, the overhead of fully reproducible tracing may only be acceptable at the time of in-house testing.
In this talk, I will introduce a reverse execution technique, which takes as input a core dump, reversely executes the corresponding crashing program and automatically pinpoints the root cause of the vulnerable site hidden behind the crash. In the process of performing reverse execution, our technique typically encounters uncertainty (e.g., uncertain control or data flow) which significantly influence the capability of identifying vulnerabilities. Therefore, as part of the talk, I will also briefly discuss how we utilize deep recurrent neural network to tackle this technical challenge.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Dr. Xinyu Xing is an Assistant Professor at the Pennsylvania State University. His research interest includes exploring, designing and developing tools to automate vulnerability discovery, failure reproduction, vulnerability diagnosis (and triage), exploit and security patch generation. Recently, he is also interested in developing deep learning techniques to perform highly accurate binary and malware analysis. His past research has been featured by many mainstream medium, such as Technology Review, New Scientists and NYTimes etc. Going beyond academic research, he also actively participates and hosts many world-class cybersecurity competitions (such as HITB and XCTF). This year, his team was selected for DEFCON/GeekPwn CAAD challenge grand final at Las Vegas. He led Penn State to finish NSA code breaker competition 2017 and ranked at the top 3 nationwide. In the white-hat hacker community, his research team has contributed many CVEs for the open source community. The tools his team developed have been downloaded by thousands of developers and security researchers.
Host: Muhammad Naveed
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Computer Science Department
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Mork Family Department of Chemical Engineering and Materials Science Seminar - Distinguished Lecture Series
Tue, Oct 09, 2018 @ 04:00 PM - 05:20 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Dr. Vivian Ferry, Department of Chemical Engineering and Materials Science, University of Minnesota
Talk Title: Optical nanomaterials: chirality, refractive index, and applications to solar energy conversion
Abstract: Optical nanomaterials offer the ability to bend, twist, guide, and confine light in nanoscale dimensions, leading to new applications in photovoltaics, sensing, light emission control, and other optoelectronic devices. The first part of this talk will discuss strategies for capturing and managing incident sunlight effectively for solar energy conversion. I will discuss complementary strategies for managing incident sunlight before it interacts with the solar panel, including luminescent solar concentrators that down shift and concentrate sunlight using a combination of luminescent nanocrystals and nanostructured surfaces, and structures that integrate with photovoltaic modules for thermal management. The second part of the talk will discuss the development of chiral nanomaterials that interact selectively with right and left handed circularly polarized light. I will discuss strategies to tune the chiral optical response of both semiconductor nanocrystals and metamaterials.
Biography: Vivian Ferry is an assistant professor at the University of Minnesota in the Department of Chemical Engineering and Materials Science. She received her S. B. in Chemistry from the University of Chicago in 2006, and her Ph.D. in Chemistry from the California Institute of Technology in 2011, working with Prof. Harry Atwater. She was a postdoctoral fellow with Prof. Paul Alivisatos in the Materials Science Division at Lawrence Berkeley National Laboratory from 2011 to 2014. Her research focuses on light matter interactions in nanoscale materials, and her specific research interests include light management in solar energy conversion, switchable metamaterials, and nanoscale chirality. She is the recipient of an NSF CAREER award, an Air Force Office of Scientific Research Young Investigator Award, was named as one of Technology Reviews 35 Innovators under 35 in 2016, and holds a McKnight Land Grant Professorship at the University of Minnesota.
Host: Professor Malancha Gupta
Location: John Stauffer Science Lecture Hall (SLH) - 200
Audiences: Everyone Is Invited
Contact: Karen Woo/Mork Family
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CS Colloquium: Simone Silvetti and Laura Nenzi
Wed, Oct 10, 2018 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Simone Silvetti (Numerical Methods Group) and Laura Nenzi (TU Wien),
Talk Title: Talk1: Combining Active learning optimization and Temporal logic for parameter synthesis and falsification of Complex Systems Talk 2: System Design of Stochastic Models using Robustness of Temporal Properties
Series: Computer Science Colloquium jointly with CCI-MHI Cyber-Physical Systems Seminar
Abstract: We are pleased to announce two talks during this colloquium.
Talk 1: Combining Active learning optimization and Temporal logic for parameter synthesis and falsification of Complex Systems
In this talk, we discuss the combination of Active Learning Optimization and temporal logic to the falsification and parameter synthesis of complex dynamical systems. First, we introduce Gaussian Processes and an active learning approach aimed to falsify a black box model with time-dependent functional inputs. Second, we introduce a technique also base on Gaussian Processes, named Smoothed Model Checking, which is able to estimate the probability that a stochastic system satisfies a temporal logic formula. We leverage this estimation ability and an active learning approach to find regions of the parameter space where the model satisfies a temporal logic formula with probability greater (or less) than a given threshold.
Talk 2: System Design of Stochastic Models using Robustness of Temporal Properties
In the last years, researchers from the verification community have proposed several notions of robustness for temporal logic providing suitable definitions of distance between a trajectory of a (deterministic) dynamical system and the boundaries of the set of trajectories satisfying the property of interest. In this talk, we present an extension of this notion of robustness to stochastic systems, showing that this naturally leads to a distribution of robustness degrees. Then, we show how to exploit this notion to address the system design problem, where the goal is to optimise some control parameters of a stochastic model in order to maximise robustness of the desired specifications. The key idea is to use a learning algorithm to estimate the dependence of the average robustness of a qualitative formula over the model parameters. A powerful and provably convergent machine learning method, namely the Gaussian Process - Upper Confidence Bound (GP-UCB) algorithm is use to improve the parameter optimisation. Finally, we demonstrate the applicability of our method on a number of case studies and ongoing works.
This lecture satisfies requirements for CSCI 591: Research Colloquium. Please note, due to limited capacity in OHE 100D, seats will be first come first serve.
Biography: Talk 1: Simone Silvetti is a researcher and developer at the Numerical Methods Group of Esteco SpA, Italy. He received a Ph.D. in Computer Science from the University of Udine in 2018 and a MSc in Mathematics from the University of Rome in 2012. His research focuses on the application of machine learning to quantitative formal methods and optimization.
Talk 2: Since 2017, Laura Nenzi is a research assistant at the TU Wien. She received a Ph.D in Computer Science from IMT Lucca, in 2016. In December 2018, she will join the University of Trieste as Assistant Professor. Her research interests include: spatio-temporal logics, statistical verification routines for uncertain models and combination of formal methods with machine learning techniques.
Host: Jyotirmoy Deshmukh and Paul Bogdan
Location: Olin Hall of Engineering (OHE) - 100D
Audiences: Everyone Is Invited
Contact: Computer Science Department
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Joint Epstein Institute, ISE 651 & USC CAIS Seminar
Wed, Oct 10, 2018 @ 04:00 PM - 05:00 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Pinar Keskinocak, Professor, Georgia Tech
Talk Title: Quantitative Models for Decision-support in Healthcare Applications
Host: Dr. Sze-chuan Suen
More Information: October 10, 2018.pdf
Location: Mark Taper Hall Of Humanities (THH) - 301
Audiences: Everyone Is Invited
Contact: Grace Owh
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CAIS Seminar: Dr. Pinar Keskinocak (Georgia Tech) - Quantitative Models for Decision-Support in Healthcare Applications
Wed, Oct 10, 2018 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Pinar Keskinocak, Georgia Institute of Technology
Talk Title: Quantitative Models for Decision-Support in Healthcare Applications
Series: USC Center for Artificial Intelligence in Society (CAIS) Seminar Series
Abstract: With the goal of improving patient outcomes, efficiency, and effectiveness, quantitative models are increasingly used for decision-support in healthcare. In this presentation Dr. Keskinocak will discuss a few applications from organ transplant, vaccination, screening, and workforce allocation decisions.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Dr. Pinar Keskinocak is the William W. George Chair and Professor in the School of Industrial and Systems Engineering, and co-founder and Director of the Center for Health and Humanitarian Systems at Georgia Tech. She also serves as the College of Engineering ADVANCE Professor. Her research focuses on the applications of quantitative methods to have a positive impact in society, particularly in healthcare and humanitarian systems. She has worked on projects with a variety of governmental and non-governmental organizations, and healthcare providers, including American Red Cross, CDC, Children's Healthcare of Atlanta, Emory Healthcare, and Task Force for Global Health.
Host: Dr. Milind Tambe and Dr. Sze-chuan Suen
Location: Mark Taper Hall Of Humanities (THH) - 301
Audiences: Everyone Is Invited
Contact: Computer Science Department
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Multimodal Emotion Recognition: Quantifying Dynamics and Structure in Audio-Visual Expressive Speech
Thu, Oct 11, 2018 @ 02:00 PM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Yelin (Lynn) Kim, Ph.D., Assistant Professor, University at Albany, SUNY
Talk Title: Multimodal Emotion Recognition: Quantifying Dynamics and Structure in Audio-Visual Expressive Speech
Abstract: The rise of AI assistant systems, including Google Home, Apple Siri, and Amazon Echo, brings the urgent need for increased and deeper understanding of users. In this talk, I will present algorithmic and statistical methods for analyzing audio-visual human behavior, particularly focusing on emotional and social signals inferred from speech and facial expressions. These methods can provide emotional intelligence to AI systems. However, developing automatic emotion recognition systems is challenging since emotional expressions are complex, dynamic, inherently multimodal, and are entangled with other factors of modulation (e.g. speech generation and emphasis). I will present several algorithms to address these fundamental challenges in emotion recognition: (i) cross-modal modeling methods that capture and control for interactions between individual facial regions and speech using the Minimum Description Length (MDL) principle-based segmentation; (ii) localization and prediction of events with salient emotional behaviors using a max-margin optimization and dynamic programming; and (iii) temporal modeling methods to learn co-occurrence patterns between emotional behaviors and emotion label noise. These algorithms have enabled advancements in the modeling of audio-visual emotion recognition systems and increased the understanding of the underlying dynamic and multimodal structure of affective communication (e.g., cross-modal interaction, temporal structure, and inherent perceptual ambiguity).
Biography: Yelin Kim [http://yelinkim.com] is an Assistant Professor in the Department of Electrical and Computer Engineering at the University at Albany, State University of New York (SUNY). She received her M.S. and Ph.D. in Electrical and Computer Engineering from the University of Michigan, Ann Arbor in 2013 and 2016, respectively, and her B.S. in Electrical and Computer Engineering from Seoul National University, South Korea in 2011. Her main research interests are in human-centered and affective computing, multimodal (audio-visual) modeling, and computational behavior analysis. Her work was recognized by several awards, including a Google Faculty Research Award (2018), a SUNY-A Faculty Research Award (2017), and the Best Student Paper Award at ACM Multimedia (2014).
Host: Dr. Shrikanth Narayanan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Tanya Acevedo-Lam/EE-Systems
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Auto-Tuned Threading for OLDI Microservices
Thu, Oct 11, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Akshitha Sriraman, University of Michigan
Talk Title: Auto-Tuned Threading for OLDI Microservices
Abstract: Modern On-Line Data Intensive (OLDI) applications have evolved from monolithic systems to instead comprise numerous, distributed microservices interacting via Remote Procedure Calls (RPCs). Microservices face sub-ms RPC latency goals, much tighter than their monolithic ancestors that must meet >=100ms latency targets. Sub-ms-scale threading and on currency design effects as well as OS and network overheads that were once insignificant for such monoliths, can now come to dominate in the sub-ms-scale microservice regime. It is therefore vital to characterize the influence of threading design, OS, and network effects on microservices. Unfortunately, widely used academic data center benchmark suites are unsuitable to aid this characterization as they use monolithic rather than microservice architectures.
We first investigate how OS/network overheads impact microservice tail latency by developing a complete suite of microservices called mSuite that we use to facilitate our study. Our characterization reveals that the relationship between optimal OS/network parameters and service load is complex. Our primary finding is that non-optimal OS scheduler decisions can degrade microservice tail latency by up to ~87%.
Secondly, we investigate how threading design critically impacts microservice tail latency by developing a taxonomy of threading models -“ a structured understanding of the implications of how microservices manage concurrency and interact with RPC interfaces under wide-ranging loads. We develop mTune, a system that has two features: (1) a novel framework that abstracts threading model implementation from application code, and (2) a novel automatic load adaptation system that curtails microservice tail latency by exploiting inherent latency trade-offs revealed in our taxonomy to transition among threading models. We study mTune in the context of mSuite to demonstrate up to 1.9x tail latency improvements over static threading choices and state-of-the-art adaptation techniques.
Biography: Akshitha is a fourth year Ph.D. student at the University of Michigan, where she is advised by Dr. Thomas F. Wenisch. Her primary research interests are in software systems and computer architecture. Her research focuses on developing software and hardware optimizations to improve the performance of large-scale distributed data center system.
Host: Xuehai Qian, xuehai.qian@usc.edu
More Information: 18.10.11 Akshitha Sriraman_CENG.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Brienne Moore
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BME seminars
Thu, Oct 11, 2018 @ 03:00 PM - 04:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Abstract: Over the past decade we have been working to develop functional and molecular imaging technologies for a variety of applications. A current focus is technologies capable of functional imaging of picometer scale vibrations in the ear. This collaboration with researchers in otolaryngology has led to several recent papers that contribute new understandings of inner ear function. These were enabled by our development of Optical Coherence Tomography (OCT) as a highly sensitive spatially resolved vibrometer. Building on this approach, we have begun to develop devices to fill unmet clinical needs for diagnosis and therapeutic guidance in humans. The first of those devices (cochleoscope) is an endoscopic OCT system designed to traverse the human ear canal and peer into the inner ear through the round window. This device would be used clinically to identify endolymphatic hydrops, anomalous vibratory response, and ischemia of the inner ear. We recently demonstrated this device in a porcine model and have IRB approval for a first-in-human trial at USC. A second device attaches to the standard operating microscopes in the hearing clinic, enabling noninvasive imaging of middle ear morphology and function. In vivo human testing of this device has shown that we can achieve a sensitivity to vibrations of of
More Information: Brian E. Applegate Flyer.pdf
Location: 145a
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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Munushian Seminar - Demetrios Christodoulides, Friday, October 12th at 2PM in EEB 132
Fri, Oct 12, 2018 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Demetrios Christodoulides, CREOL The College of Optics and Photonics
Talk Title: Optical Thermodynamics of Nonlinear Highly Multimode Systems
Abstract: The past few years have witnessed a resurgence of interest in multimode waveguide structures, predominantly driven by the ever-increasing demand for higher information capacities. This renaissance, in turn, incited a flurry of activities in the general area of nonlinear multimode fiber optics. The sheer complexity associated with the presence of hundreds or thousands of nonlinearly interacting modes that collectively act as a many-body system, has led to new opportunities in observing a multitude of novel optical effects that would have been otherwise impossible in single-mode settings. In this talk, a thermodynamic theory capable of describing complex, highly multimoded, nonlinear optical systems is presented. It is shown that the mode occupancies in such nonlinear multimode arrangements follow a universal behavior that always tends to maximize the system's entropy at steady-state. This thermodynamic response takes place irrespective of the type of nonlinearities involved and can be utilized to either heat or cool an optical multimode system. Aspects associated with adiabatic compressions and expansions will be discussed along with the possibility for all-optical Carnot cycles.
Biography: Biography: Demetrios Christodoulides is the Cobb Family Endowed Chair and Pegasus Professor of Optics at CREOL-the College of Optics and Photonics of the University of Central Florida. He received his Ph.D. degree from Johns Hopkins University in 1986 and he subsequently joined Bellcore as a post-doctoral fellow. Between 1988 and 2002 he was with the faculty of the Department of Electrical Engineering at Lehigh University. His research interests include linear and nonlinear optical beam interactions, synthetic optical materials, optical solitons, and quantum electronics. He has authored and co-authored more than 350 papers. He is a Fellow of the Optical Society of America and the American Physical Society. He is the recipient of the 2011 Wood Prize and 2018 Max Born Award of OSA.
Host: EE-Electrophysics
More Info: https://minghsiehee.usc.edu/about/lectures/munushian/
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: https://minghsiehee.usc.edu/about/lectures/munushian/
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Quantum Supremacy and its Applications
Fri, Oct 12, 2018 @ 02:30 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Scott Aaronson, University of Texas at Austin
Talk Title: Quantum Supremacy and its Applications
Abstract: In the near future, there will likely be special-purpose quantum computers with 50-70 high-quality qubits and controllable nearest-neighbor couplings. In this talk, I'll discuss general theoretical foundations for how to use such devices to demonstrate quantum supremacy: that is, a clear quantum speedup for some task, motivated by the goal of overturning the Extended Church-Turing Thesis (which says that all physical systems can be efficiently simulated by classical computers) as confidently
as possible. This part of the talk is based on joint work with Lijie
Chen. Then, in a second part, I'll discuss new, not-yet-published work on how these experiments could be used to generate cryptographically certified random bits, for use in cryptocurrencies and other applications.
Biography: Scott Aaronson is David J. Bruton Centennial Professor of Computer Science at the University of Texas at Austin. He received his bachelor's from Cornell University and his PhD from UC Berkeley, and did postdoctoral fellowships at the Institute for Advanced Study as well as the University of Waterloo. Before coming to UT Austin, he spent nine years as a professor in Electrical Engineering and Computer Science at MIT. Aaronson's research in theoretical computer science has focused mainly on the capabilities and limits of quantum computers. His first book, Quantum Computing Since Democritus, was published in 2013 by Cambridge University Press. He received the National Science Foundation Alan T. Waterman Award, the United States PECASE Award, the Vannevar Bush Fellowship, the Tomassoni-Chisesi Prize in Physics, and MIT's Junior Bose Award for Excellence in Teaching.
Host: Xuehai Qian, xuehai.qian@usc.edu
More Information: 18.10.12 Scott Aaronson Seminar .pdf
Location: Ronald Tutor Hall of Engineering (RTH) - 109
Audiences: Everyone Is Invited
Contact: Brienne Moore
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NL Seminar-Mapping Functions for Multilingual Word Embeddings
Fri, Oct 12, 2018 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Ndapa Nakashole, UCSD
Talk Title: Mapping Functions for Multilingual Word Embeddings
Series: Natural Language Seminar
Abstract: Inducing multilingual word embeddings by learning a linear map between embedding spaces of different languages achieves remarkable accuracy on related languages. However, accuracy drops substantially when translating between distant languages. Given that languages exhibit differences in vocabulary, grammar, written form, or syntax, one would expect that embedding spaces of different languages have different structures especially for distant languages. I will present our work on understanding the behavior of linear maps learned by word translation methods. Additionally, I will present some initial solutions to the shortcomings of such linear maps.
Biography: Ndapa Nakashole is an Assistant Professor in the Department of Computer Science and Engineering at the University of California, San Diego. Prior to UCSD, she was a Postdoctoral Fellow in the Machine Learning Department at Carnegie Mellon University. She obtained her PhD from Saarland University, Germany, for research carried out at the Max Planck Institute for Informatics in Saarbrücken. She completed undergraduate studies in Computer Science at the University of Cape Town, South Africa.
Host: Xusen Yin
More Info: http://nlg.isi.edu/nl-seminar/
Webcast: https://bluejeans.com/s/R09BB/Location: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, Marina Del Rey
WebCast Link: https://bluejeans.com/s/R09BB/
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://nlg.isi.edu/nl-seminar/
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CS Colloquium: Judea Pearl (UCLA) - The New Science of Cause and Effect
Mon, Oct 15, 2018 @ 12:00 PM - 01:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Professor Judea Pearl, UCLA
Talk Title: The New Science of Cause and Effect
Series: Computer Science Colloquium
Abstract: Professor Judea Pearl's talk will summarize a revolution that has changed the way scientists deal with cause-effect questions and that will have profound effects on our future. Pearl will first describe how hard causal questions that long were regarded as
either metaphysical or unmanageable can now be solved using elementary steps and what this tells us about how our mind achieves causal understanding. He will then outline how robots can be built that learn to communicate in our language of cause and effect and reason counterfactually about credit and blame, regret, intent and responsibility.
This lecture satisfies requirements for CSCI 591: Research Colloquium
This talk is co-sponsored by: USC Viterbi Department of Computer Science, USC Annenberg School for Communication and Journalism, USC Marshall Department of Data Sciences and Operations and USC Dornsife Department of Economics.
Biography: Judea Pearl is a professor of computer science and statistics at UCLA, where he directs the Cognitive Systems Laboratory and conducts research in artificial intelligence, human cognition, and philosophy of science. Pearl is the 2011 recipient of the ACM Alan Turing Award, and the 2002 London School of Economics Lakatos Award in the philosophy of science. He is the author of Heuristics (1983), Probabilistic Reasoning (1988), Causality (2000, 2009) and most recently co-authored The Book of Why (2018).
Host: Computer Science Department and School of Communication in Annenberg
Location: Wallis Annenberg Hall (ANN) 106 (Sheindlin Forum)
Audiences: Everyone Is Invited
Contact: Computer Science Department
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Seminars in Biomedical Engineering
Mon, Oct 15, 2018 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Hanming Peng, USC Visiting Professor
Talk Title: Drug delivery for cancer application
Host: Qifa Zhou
Location: Olin Hall of Engineering (OHE) - 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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Fall 2018 Joint CSC@USC/CommNetS-MHI Seminar Series
Mon, Oct 15, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Stanley Chan, Purdue University
Talk Title: Understanding Plug-and-Play ADMM: Convergence, Objective Function, and Generalization
Abstract: The Plug-and-Play (PnP) ADMM algorithm is a recently developed image restoration method that allows advanced image denoisers to be integrated into physical forward models to yield a provable convergent algorithm. Since its introduction in 2013, PnP ADMM has enabled numerous record-breaking image recovery results in deblurring, inpainting, super-resolution, Poisson denoising, and compressed sensing, etc. However, despite the successful applications and promising results, very little is known about why PnP ADMM performs so well. Fundamentally, the challenge lies in the fact that many of the latest denoisers are not easily expressible as proximal maps, e.g., deep neural networks.
In this talk, I will highlight a few recent progresses made by my group and collaborators. I will discuss three questions. (1) Convergence: Under what conditions of the denoisers will PnP ADMM converge? Answering this question will allow us to comment on what kind of denoisers we can use and what kind of convergence we should expect. (2) Objective Function: By plugging in an off-the-shelf denoiser, what does PnP ADMM actually solve? That is, what is the corresponding objective function? This problem will tell us why and when PnP ADMM will perform well, and when PnP ADMM will fail. (3) Generalization: Are we able to generalize PnP ADMM to accommodate multiple agents beyond a single forward model and a single denoiser? This leads to a new concept called consensus equilibrium, which allows us to integrate multiple weak experts to produce an overall strong recovery method. I will illustrate the ideas through examples in image denoising, graph signal processing, turbulence removal and automatic foreground extraction.
Biography: Stanley H. Chan is currently an Assistant Professor in the School of Electrical and Computer Engineering and the Department of Statistics at Purdue University, West Lafayette, IN. He received the B.Eng. degree in Electrical Engineering from the University of Hong Kong in 2007, the M.A. degree in Mathematics from UC San Diego in 2009, and the Ph.D. degree in Electrical Engineering from UC San Diego in 2011. In 2012-2014, he was a postdoctoral research fellow at Harvard. His PhD study and postdoctoral training were supported by the Croucher Foundation PhD Scholarship and postdoctoral Fellowship, two of the most prestigious scholarships in Hong Kong.
Dr. Chan is a recipient of the Best Paper Award of IEEE International Conference on Image Processing 2016 for his work on single photon image sensors. He is also a recipient of multiple education awards including the IEEE Signal Processing Cup Second Prize, Purdue College of Engineering Outstanding Graduate Mentor Award, Eta Kappa Nu Teaching Award, Eta Kappa Nu Outstanding Professor Award, and Purdue Teaching for Tomorrow Fellowship.
Dr. Chan is an Associate Editor of IEEE Transactions on Computational Imaging since 2018, an Associate Editor of OSA Optics Express in 2016 - 2018, an Elected Member and the subcommittee Chair of the IEEE Signal Processing Society Special Interest Group in Computational Imaging since 2015. He was the co-chair and co-organizer of the computational imaging special session in ICIP 2016, and had served on multiple technical program committees including ICIP, ICASSP, OSA Imaging and Applied Optics Congress, and Midwest Machine Learning Symposium.
Host: Antonio Ortega, antonio.ortega@sipi.usc.edu
More Info: http://csc.usc.edu/seminars/2018Fall/chan.html
More Information: 18.10.15 Stanley Chan_CSC@USC Seminar.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Brienne Moore
Event Link: http://csc.usc.edu/seminars/2018Fall/chan.html
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Finding Structure in Data: Clustering and Representation Learning
Tue, Oct 16, 2018 @ 10:00 AM - 11:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Arya Mazumdar, College of Information & Computer Sciences, University of Massachusetts Amherst
Talk Title: Finding Structure in Data: Clustering and Representation Learning
Abstract: This talk is loosely divided into two parts, both about uncovering hidden structures in data by unsupervised or semisupervised methods. In the first, we discuss new tools to learn parameters of mixtures of distributions, statistical block models, and interactive algorithms for such problems. In the second, we describe new algorithms to learn nonlinear models of data, primarily focusing on networks of rectified linear units. We will emphasize on the information theoretic tools that have been used in both of the parts. We provide rigorous theoretical guarantees and our algorithms perform very well in experiments conducted with real data.
Biography: Arya Mazumdar is an assistant professor in the College of Information and Computer Sciences at the University of Massachusetts Amherst since Fall 2015. Prior to this, Arya was an assistant professor at the University of Minnesota-Twin Cities, and a postdoctoral scholar at Massachusetts Institute of Technology. Arya received his Ph.D. from the University of Maryland, College Park, in 2011, where his thesis won the Distinguished Dissertation Fellowship Award. Arya is a recipient of the 2015 NSF CAREER award and the 2010 IEEE ISIT Jack K. Wolf Student Paper Award. He spent the summers of 2008 and 2010 at the Hewlett-Packard Laboratories, Palo Alto, CA, and IBM Almaden Research Center, San Jose, CA, respectively. Arya's research interests include information theory and machine learning.
Host: Professor Salman Avestimehr
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Talyia White
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Epstein Institute Seminar - ISE 651
Tue, Oct 16, 2018 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Andrzej Ruszczynski , Professor, Rutgers Business School
Talk Title: Risk-Averse Optimization and Control of Partially Observable Systems
Host: Dr. Meisam Razaviyayn
More Information: October 16, 2018.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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Mork Family Department of Chemical Engineering and Materials Science Seminar - Lyman L. Handy Colloquia
Tue, Oct 16, 2018 @ 04:00 PM - 05:20 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Professor Susanne Stemmer, Materials Department , University of California, Santa Barbara
Talk Title: Topological Heterostructures by Molecular Beam Epitaxy
Abstract: Topology, both in real space and in reciprocal space, has emerged as a new design principle for materials that can host a wealth of novel properties. Interfaces and heterostructures with topological materials offer opportunities to control and manipulate their electronic states and associated phenomena, for example, via electric field effect, strain, or symmetry breaking. In this presentation, we will discuss recent progress in the growth of thin films of the three-dimensional Dirac semimetal Cd3As2 by molecular beam epitaxy. We show that high-mobility, epitaxial Cd3As2 films can be grown and discuss some of the phenomena that can be observed, such as an unusually large negative longitudinal magnetoresistance under parallel electric and magnetic fields. The heterostructures allow for experimental tests of theoretically predicted transitions between topological states by manipulating parameters, such as confinement and film strain. For example, as the film thickness is reduced, a band gap opens in the bulk Dirac electronic states and we observe a quantum Hall effect. Using electric field gating and Landau level spectroscopy, we demonstrate the Dirac dispersion of these two-dimensional states.
Biography: Susanne Stemmer is Professor of Materials at the University of California, Santa Barbara. She did her doctoral work at the Max-Planck Institute for Metals Research in Stuttgart (Germany) and received her degree from the University of Stuttgart in 1995. Following postdoctoral positions, she moved to Rice University, where she was Assistant Professor from 1999 to 2002. In 2002, she joined the University of California, Santa Barbara. Her research interests are in the development of scanning transmission electron microscopy techniques, molecular beam epitaxy, functional and strongly correlated oxide heterostructures, and topological materials. She has authored or co-authored more than 240 publications. Honors include election to Fellow of the American Ceramic Society, Fellow of the American Physical Society, Fellow of the Materials Research Society, Fellow of the Microscopy Society of America, and a Vannevar Bush Faculty Fellowship of the Department of Defense.
Host: Dr. Jayakanth Ravichandran
Location: John Stauffer Science Lecture Hall (SLH) - 200
Audiences: Everyone Is Invited
Contact: Karen Woo/Mork Family
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Machine-Integrated Intelligence, Controlled Sensing, and Active Learning
Wed, Oct 17, 2018 @ 12:00 AM - 01:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Tara Javidi, Electrical and Computer Engineering, UC San Diego
Talk Title: Machine-Integrated Intelligence, Controlled Sensing, and Active Learning
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: The computing landscape has been drastically changing. The new computing realm, which is sometimes dubbed as internet of everything, includes networked devices ranging from tiny wearable sensors, smart home appliances, and personal autonomous robots, to connected self-driving cars, and to smart city infrastructures. In this new computing eco-system, comprising of resource-constrained, unreliable, and vulnerable components and networks, the non-recurring cost of hardware acceleration, engineering implementation, and system building has continued to grow significantly. This is in addition to the growing cost associated with the collection, curation, and labeling of data during both the training and the execution of various popular machine learning models. These design bottle-necks not only result in a significant increase in the non-recurring cost of engineering for companies but also provide a severe hurdle in technology development associated with hardware upgrade and/or system redesign.
In the first part of the talk, I will discuss an overview of my research on information acquisition and active learning in the context of the mission of our newly formed UCSD Center for Machine-Integrated Computing and Security (MICS). I will report ongoing research in the center where this system integrated view has enabled best-in-class results by bringing Machine into Machine Learning. In the second part of the talk, I will delve deeper into the problems of information acquisition, controlled sensing, and active learning and show our solutions to significantly reduce the cost of data collection and/or data labeling while ensuring reliability and fidelity during the training or run-time. In particular, we illustrate our findings and algorithms in the context of DetecDrone: an ML-enabled drone intelligence platform developed in my lab to provide search, mapping, and monitoring off-the-shelf low cost drones.
Biography: Tara Javidi studied electrical engineering at Sharif University of Technology, Tehran, Iran from 1992 to 1996. She received her MS degrees in electrical engineering (systems) and in applied mathematics (stochastic analysis) from the University of Michigan, Ann Arbor, in 1998 and 1999, respectively. She received her Ph.D. in electrical engineering and computer science from the University of Michigan, Ann Arbor, in 2002. From 2002 to 2004, Tara Javidi was an assistant professor at the Electrical Engineering Department, University of Washington, Seattle. In 2005, she joined the University of California, San Diego, where she is currently a professor of electrical and computer engineering and a founding co-director of the Center for Machine-aware Computing and Security (MICS). She is also a member of Board of Governors of the IEEE Information Theory Society (2017/18/19).
Tara Javidi's research interests are in theory of active learning, information theory with feedback, stochastic control theory, and stochastic resource allocation in wireless communications and communication networks. Tara Javidi was a recipient of a 2018 Qualcomm Faculty Award, National Science Foundation early career award (CAREER) in 2004, Barbour Graduate Scholarship, University of Michigan, in 1999, and the Presidential and Ministerial Recognitions for Excellence in the National Entrance Exam, Iran, in 1992. Tara Javidi is a Distinguished Lecturer of the IEEE Information Theory Society (2017/18).
Host: Professor Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia Whtie
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CS Colloquium: Fred Morstatter (USC-ISI) - Discovering, Mitigating and Characterizing Social Data Bias
Wed, Oct 17, 2018 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Fred Morstatter, USC - ISI
Talk Title: Discovering, Mitigating and Characterizing Social Data Bias
Series: CS Colloquium
Abstract: Researchers and practitioners use social media to extract actionable patterns about human behavior. However, biases are inevitable and can either be a hindrance or an asset to such analysis. In this talk, I will discuss perturbations to the underlying data that can lead to flawed analysis. I will show how common assumptions in handling social media data can lead to flawed research results, and suggest approaches to combat these problems. However, if we understand the biases in our dataset it can lead to deeper understanding of the populations we wish to study. Once the biases underlying a social dataset are recognized, researchers are in a better position to study the unique characteristics underlying different cultural groups. This talk will conclude with a discussion of ways to identify cultural groups online and to characterize the biases between them.
This lecture satisfies requirements for CSCI 591: Research Colloquium. Please note, due to limited capacity, seats will be first come first serve.
Biography: Fred Morstatter is a Computer Scientist at the Information Science Institute. His research focuses on understanding biases that occur in online social data. Specifically, he is interested in biases that can skew research results from big social data. He is also interested in characterizing the biases of cultural groups based upon the trace data they create on social media. He has been a key contributor to the Synergistic Anticipation of Geopolitical Events (SAGE) project under IARPA's Hybrid Forecasting Competition. This project combines human judgement with machine forecasts of geopolitical events in the form of a web platform that serves as a vehicle for research in social media mining. He has published in JMLR, WWW, KDD and ICWSM, among others. He is Program Committee Chair for ICWSM 2019. A full list of publications can be found at www.fredmorstatter.com. Contact him at fredmors@isi.edu.
Host: Computer Science
Location: Olin Hall of Engineering (OHE) - 100D
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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CAIS Seminar: Dr. John Prindle (USC) – Predicting Risk of Future Child Welfare Involvement
Wed, Oct 17, 2018 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. John Prindle, USC
Talk Title: Predicting Risk of Future Child Welfare Involvement
Series: USC Center for Artificial Intelligence in Society (CAIS) Seminar Series
Abstract: Child maltreatment impacts a significant number of children per year and is typically not limited to one encounter with the system. Past records provide a wealth of information which may be used to supplement current maltreatment allegations. Machine learning algorithms in the form of Random Forests were applied to these data to predict risk of future child welfare outcomes, past and present factors.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Dr. John Prindle is a research assistant professor with the Children's Data Network at USC. His current work focuses on the impact of childhood maltreatment on downstream services such as education and medical services.
Host: Milind Tambe
Location: Mark Taper Hall Of Humanities (THH) - 301
Audiences: Everyone Is Invited
Contact: Computer Science Department
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CS Colloquium: Steve Chien (JPL) - The Growing Role for Artificial Intelligence in Space Exploration and the Search for Life Beyond Earth
Wed, Oct 17, 2018 @ 05:00 PM - 06:30 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Steve Chien, Jet Propulsion Laboratory, California Institute of Technology
Talk Title: The Growing Role for Artificial Intelligence in Space Exploration and the Search for Life Beyond Earth
Series: Computer Science Colloquium
Abstract: Artificial Intelligence is playing an increasing role in our everyday lives and the business marketplace. This trend extends to the space sector, where AI has already shown considerable success and has the potential to revolutionize almost every aspect of space exploration. I first highlight a number of success stories of the tremendous impact of Artificial Intelligence in Space: over a dozen years of operations of the Autonomous Sciencecraft on EO-1, the Earth Observing Sensorweb tracking volcanoes, flooding and wildfires and automated targeting onboard the MSL Curiosity rover. Next I describe several search and optimization formulations of space scheduling problems: data management for spacecraft and observation scheduling. Finally I discuss why AI is critical to search for life beyond Earth, highlighting the role of AI in Europa Submersible and Interstellar mission concepts.
RSVP: https://goo.gl/forms/iLw0LrMKq6JvqxkD3
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Dr. Steve Chien is a Senior Research Scientist at the Jet Propulsion Laboratory, California Institute of Technology where he leads efforts in autonomous systems for space exploration. Dr. Chien has received numerous awards for his research in space autonomous systems including: NASA Medals in 1997, 2000, 2007, and 2015; he is a four time honoree in the NASA Software of the Year competition (1999, 1999, 2005, 2011); and in 2011 he was awarded the inaugural AIAA Intelligent Systems Award. He has led the deployment of ground and flight autonomy software to numerous missions including the Autonomous Sciencecraft/Earth Observing One, WATCH/Mars Exploration Rovers, Earth Observing Sensorwebs, IPEX, and ESA's Rosetta.
Host: AAAI@USC
Location: Mark Taper Hall Of Humanities (THH) - 101
Audiences: Everyone Is Invited
Contact: Computer Science Department
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Stochastic Control of Finite and Infinite Dimensional Systems Under Uncertainty: Theory, Algorithms and Applications
Thu, Oct 18, 2018 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Evangelos A. Theodorou , Guggenheim School of Aerospace Engineering, Georgia Institute of Technology
Talk Title: Stochastic Control of Finite and Infinite Dimensional Systems Under Uncertainty: Theory, Algorithms and Applications
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: In this talk, I will present an overview of projects related to stochastic control and machine learning methods and their applications to dynamical systems represented by stochastic differential and stochastic partial differential equations. These are typically systems that exists in autonomy and robotics as well as in areas of applied physics such as fluid mechanics, plasma physics and turbulence. I will discuss different forms of uncertainty representation that span Gaussian Processes, Polynomial Chaos, Deep Probabilistic Neural Networks and Q-Wiener processes. Finally, I will show applications to robotic terrestrial agility, perceptual control, social networks, large-scale swarms, and control of stochastic fields, and conclude with future directions.
Biography: Evangelos A. Theodorou is an assistant professor with the Guggenheim School of aerospace engineering at Georgia Institute of Technology. He is also affiliated with the Institute of Robotics and Intelligent Machines. Evangelos Theodorou earned his Diploma in Electronic and Computer Engineering from the Technical University of Crete (TUC), Greece in 2001. He has also received a MSc in Production Engineering from TUC in 2003, a MSc in Computer Science and Engineering from University of Minnesota in spring of 2007 and a MSc in Electrical Engineering on dynamics and controls from the University of Southern California(USC) in Spring 2010. In May of 2011 he graduated with his PhD, in Computer Science at USC. After his PhD, he was a Postdoctoral Research Fellow with the department of computer science and engineering, University of Washington, Seattle. Evangelos Theodorou is the recipient of the King-Sun Fu best paper award of the IEEE Transactions on Robotics for the year 2012 and recipient of the best paper award in cognitive robotics in International Conference of Robotics and Automation 2011. He was also the finalist for the best paper award in International Conference of Humanoid Robotics 2010, International Conference of Robotics and Automation 2017 and Robotics Science and Systems 2018. His theoretical research spans the areas of stochastic optimal control theory, machine learning, information theory and statistical physics. Applications involve learning, planning and control in autonomous, robotics and aerospace systems.
Host: Prof. Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Talyia White
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W.V.T. RUSCH ENGINEERING HONORS COLLOQUIUM
Fri, Oct 19, 2018 @ 01:00 PM - 01:50 PM
USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Jakob van Zyl , Director for Solar System Exploration, Jet Propulsion Laboratory
Talk Title: Exploring the Solar System and Beyond
Host: EHP and Dr. Prata
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Amanda McCraven
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Essentials of Composites ManufacturingSat, Oct 20, 2018 @ 08:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Abstract: Essentials of Composites Manufacturing provides a high-level overview of manufacturing science and engineering for aerospace composite structures, focusing on prepreg and liquid molding processes, including hands-on laboratory demonstrations.
Course participants will complete a multiple-choice quiz as a knowledge assessment, available online at the end of the course. When the course and quiz have been successfully completed, participants will receive USC Continuing Education Units.
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/chemical-engineering-materials-science/essentials-composites-manufacturing/
Audiences: Registered Attendees
Contact: Corporate & Professional Programs
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Seminars in Biomedical Engineering
Mon, Oct 22, 2018 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Xuejun Qian, USC Biomedical Engineering, PhD Candidate
Talk Title: High resolution vessel and elastograph imading
Host: Qifa Zhou
Location: Olin Hall of Engineering (OHE) - 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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PhD Defense
Tue, Oct 23, 2018 @ 11:00 AM - 12:00 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Mr. Anyi Zhang , PhD Student, CHE
Talk Title: 'Nanostructure Design of Sulfur Cathodes and Lithium Metal Anodes for Lithium Ion Batteries
Abstract: Lithium ion batteries (LIBs) have been successfully used in portable electronics and electric vehicles for many years. Although the demand for high energy density keeps increasing, the existing commercial LIB systems are getting close to their theoretical capacity limits. In order to push the energy density to an even higher level, lithium sulfur (Li-S) batteries attract a lot of attention due to their high energy density and low cost. In this thesis, I will discuss the current challenges we are facing in Li-S battery development and our proposed solutions to address those issues using nanostructure design.
I will first present our accomplishment to enhance the S cathode performance. We have developed a scalable and inexpensive design for S cathode by capping a flexible gel polymer / carbon nanofiber (CNF) composite membrane onto a free-standing and binder-free CNF + Li2S6 cathode, thus forming a three-dimensional (3D) structural design. While the CNF network was used as the current collector and S holder to overcome the insulating nature and volume expansion of S, the composite membrane composed of a gel polymer poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) and CNF additive was used as an interlayer to trap polysulfides and recycle remaining S species, leading to high specific capacity and long cycle life.
Next, I will talk about our achievement for stable Li metal anodes. We have demonstrated a distinctive design for dendrite-free deposition of Li by modifying the Cu current collector with a 3D CNF network. Due to the large surface area and high conductivity of the CNF network, Li metal can insert into and deposit onto CNF directly and no dendritic Li metal was observed, leaving a flat Li metal surface. The scalable preparation method and impressive results achieved here demonstrated the potential of applying our design in the development of dendrite-free Li metal anodes in future.
In addition, I will also present my research to further improve the performance of Li metal anodes. We have proposed a novel design of 3D interconnected graphene (IG) framework synthesized with the help of nickel (Ni) microspheres for stable Li metal anodes. The as-prepared IG framework consisted of multiple stacks of two-dimensional (2D) graphene layers and plenty of hollow graphene microspheres in between, and thus provided protective layers on the top to suppress lithium dendrites, sufficient surface area to reduce the effective current density, as well as ion channels for fast Li transport. This strategy of vertically stacking 2D materials provides a novel approach towards dendrite-free Li metal anodes for the next-generation energy storage systems.
Host: Dr. Chongwu Zhou
Location: Ronald Tutor Hall of Engineering (RTH) - 306
Audiences: Everyone Is Invited
Contact: Karen Woo/Mork Family
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Epstein Institute Seminar - ISE 651
Tue, Oct 23, 2018 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Julie Swann, Professor and Dept. Chair, North Carolina State University
Talk Title: Engineering Modeling to Assist in Eradication of Guinea Worm
Host: Dr. Sze-chuan Suen
More Information: October 23, 2018.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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CS Colloquium: Ioannis Mitliagkas (University of Montréal) - Negative Momentum for Improved Game Dynamics
Tue, Oct 23, 2018 @ 03:30 PM - 04:50 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Ioannis Mitliagkas, University of Montréal
Talk Title: Negative Momentum for Improved Game Dynamics
Series: Computer Science Colloquium
Abstract: Games generalize the single-objective optimization paradigm by introducing different objective functions for different players. Differentiable games often proceed by simultaneous or alternating gradient updates. In machine learning, games are gaining new importance through formulations like generative adversarial networks (GANs) and actor-critic systems. However, compared to single-objective optimization, game dynamics are more complex and less understood. In this talk, I will present recent research on the momentum dynamics of differentiable games. We will see an analysis of a simple differentiable game, which suggests that a negative momentum term can sometimes improve convergence. Then we will see empirical results that alternating gradient updates with a negative momentum term achieves convergence on the notoriously difficult to train saturating GANs.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Ioannis Mitliagkas is an assistant professor in the department of Computer Science and Operations Research (DIRO) at the University of Montréal, and member of MILA. Before that, he was a Postdoctoral Scholar with the departments of Statistics and Computer Science at Stanford University. He obtained his Ph.D. from the department of Electrical and Computer Engineering at The University of Texas at Austin. His research includes topics in statistical learning and inference, focusing on optimization, efficient large-scale and distributed algorithms, statistical learning theory and MCMC methods. His recent work includes methods for efficient and adaptive optimization, studying the interaction between optimization and the dynamics of large-scale learning systems as well as understanding and improving the performance of Gibbs samplers. In the past he has worked on high-dimensional streaming problems and fast algorithms and computation for large graph problems.
Host: Fei Sha
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Computer Science Department
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Integrating Security in Cyber-physical Systems
Wed, Oct 24, 2018 @ 12:00 PM - 01:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Miroslav Pajic, Duke University
Talk Title: : Integrating Security in Cyber-physical Systems
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: Modern embedded control architectures have moved from isolated systems to open architectures, such as new automotive systems with services that include remote diagnostics, code updates, and vehicle-to-vehicle communication. However, this increasing set of functionalities, network interoperability, and system design complexity have also introduced security vulnerabilities that are easily exploitable, since current embedded and cyber-physical systems have not been built with security in mind. Furthermore, the tight interaction between information technology and physical world makes these systems vulnerable to malicious attacks beyond the standard cyber-attacks, while relying exclusively on conventional security techniques may be unfeasible due to resource-constraints and long system lifetime.
Consequently, there is a need to change the way we reason about security in cyber-physical systems, and start designing platform-aware attack-resilient components and architectures capable of dealing with various attacks on the systems and its environment. In this talk, I will present our recent efforts in this domain, starting from cyber-physical security techniques that (a) capture effects of attacks on system performance, (b) introduce attack resilience into control algorithms and facilitate attack detection, and (c) enable mapping of the desired Quality-of-Control (QoC) under attack guarantees into real-time performance requirements on the underlying OS and networks. In addition, I will introduce a physics-aware design framework for securing resource-constrained CPS, that supports design-time tradeoffs between QoC in the presence of attacks and system resources used by the deployed security mechanisms, such as message authentication. This design framework has been used to add strong security guarantees in several existing automotive system. Finally, for systems with varying levels of autonomy and human interaction, I will show how we can exploit human power of inductive reasoning and the ability to provide context, to improve the overall security guarantees
Biography: Miroslav Pajic is the Nortel Networks Assistant Professor in Department of Electrical and Computer Engineering, Duke University, with a secondary appointment in the Computer Science Department. He received the Dipl. Ing. and M.S. degrees from the University of Belgrade, Serbia, in 2003 and 2007, as well as the M.S. and Ph.D. degrees from the University of Pennsylvania, Philadelphia, in 2010 and 2012, respectively. His research interests focus on design and analysis of cyber-physical systems (CPS) and in particular on model-based design of CPS, real-time and embedded systems, high-assurance distributed and networked control systems, and high-confidence medical devices and systems.
Miroslav received various awards including the NSF CAREER Award, ONR Young Investigator Program Award, ACM SIGBED Frank Anger Memorial Award, the Joseph and Rosaline Wolf Dissertation Award from Penn Engineering, as well as six Best Paper and Runner-up Awards at the main CPS venues, including the Best Paper Awards at the 2017 ACM SIGBED International Conference on Embedded Software (EMSOFT) and 2014 ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS), and the Best Student Paper award at the 2012 IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS).
Host: Professor Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
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CAIS Seminar: Dr. Xiang Ren (USC) - Learning Text Structures with Weak Supervision
Wed, Oct 24, 2018 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Xiang Ren, USC
Talk Title: Learning Text Structures with Weak Supervision
Series: USC Center for Artificial Intelligence in Society (CAIS) Seminar Series
Abstract: The real-world data, though massive, are hard for machines to resolve as they are largely unstructured and in the form of natural-language text. One of the grand challenges is to turn such massive corpora into machine-actionable structures. Yet, most existing systems have heavy reliance on human effort in the process of structuring various corpora, slowing down the development of downstream applications. In this talk, I will introduce an effort-light framework that extracts structured facts from massive corpora without task-specific human labeling effort. I will briefly introduce several interesting learning frameworks for structure extraction, and will share some directions towards mining corpus-specific structured networks for knowledge discovery.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Xiang Ren is an Assistant Professor in the Department of Computer Science at USC affiliated with USC ISI. Xiang was a visiting researcher at Stanford University and received his PhD in CS at UIUC. He is interested in computational methods and systems that extract machine-actionable knowledge from massive unstructured text data, and is particularly excited about problems in the space of modeling sequence and graph data under weak supervision (learning with partial/noisy labels, and semi-supervised learning) and indirect supervision (multi-task learning, transfer learning, and reinforcement learning).
Location: Mark Taper Hall Of Humanities (THH) - 301
Audiences: Everyone Is Invited
Contact: Computer Science Department
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The IEEE GRSS Chapter and University of Southern California Special Lecture Event, Wednesday, Oct. 24th at 6pm in EEB 132
Wed, Oct 24, 2018 @ 06:00 PM - 07:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Jeff Puschell,, Principal Engineering Fellow and Chief Scientist Space Systems at Raytheon Space and Airborne Systems in El Segundo
Talk Title: ATLIS: Advanced Technology Land Imaging Spectroradiometer: a Next Generation Sustainable Land Imager
Abstract: The Advanced Technology Land Imaging Spectroradiometer (ATLIS) is a small (0.04 m3), multispectral pushbroom imager to provide visible through shortwave (VSWIR) calibrated imagery for the Sustainable Land Imaging-Technology (SLI-T) reference mission architecture (RMA).
ATLIS is designed to provide imaging spectroradiometry that meets SLI-T RMA key parameters with an instrument that is much smaller and much less massive than previous land imaging systems.
This presentation describes a NASA ESTO funded project to design, build and test a six spectral band prototype ATLIS called ATLIS-P that will establish whether this compact, low mass design approach with wide field of view (WFOV), free form reflective telescope, large format, small detector digital FPA and on-chip processing meets SLI-T RMA VSWIR requirements. ATLIS is supported by NASA ESTO through grant NNX16AP64G.
Biography: Dr. Jeff Puschell is Principal Engineering Fellow and Chief Scientist, Space Systems at Raytheon Space and Airborne Systems in El Segundo, California. He is an internationally recognized expert in the system engineering of space-based imaging and remote sensing systems. His 30+ years of experience is broadly based and includes leading and making major contributions to development of visible-infrared instruments for space-based research and operational environmental imaging and remote sensing, development and field testing of laser-based communication and remote sensing systems and building and using millimeter, infrared, visible and ultraviolet wavelength instrumentation for ground-based astronomy. Dr. Puschell has been Principal Investigator, Technical Director, Chief Engineer, Chief Scientist or Project Manager on more than 15 projects in space-based remote sensing and laser communication. He has authored or co- authored 130+ papers on a variety of topics in space-based imaging and remote sensing, optical communication and astrophysics. Dr. Puschell is co-editor and co-author for the leading reference book Space Mission Engineering: The New SMAD. He is a Fellow of the AIAA and SPIE.
Host: USC Viterbi School
More Info: http://sites.ieee.org/metrola-grss/
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: http://sites.ieee.org/metrola-grss/
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NL Seminar-Conversational Question Answering
Thu, Oct 25, 2018 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Scott Yih, AI2
Talk Title: Conversational Question Answering
Series: Natural Language Seminar
Abstract: Humans seek information in a conversational manner, by asking follow-up questions for additional information based on what they have already learned. In this talk, I will first introduce the task of sequential question answering 1. which aims to fulfill user's information need by answering a series of simple, but interdependent questions regarding a given table. Treating this task as a semantic parsing problem, we developed a policy shaping mechanism that incorporates prior knowledge and an update equation that generalizes three different families of learning algorithms 2. After that, I will then talk briefly about QuAC, a new dataset for Question Answering in Context. QuAC targets the scenario where the information source is unstructured text 3. and thus can be viewed as a conversational machine comprehension task. New, unpublished model ideas will also be discussed.
Biography: Scott Wen-tau Yih is a Principal Research Scientist at Allen Institute for Artificial Intelligence AI2. His research interests include natural language processing, machine learning and information retrieval. Yih received his Ph.D. in computer science at the University of Illinois at Urbana-Champaign. His work on joint inference using integer linear programming ILP has been widely adopted in the NLP community for numerous structured prediction problems. Prior to joining AI2, Yih has spent 12 years at Microsoft Research, working on a variety of projects including email spam filtering, keyword extraction and search & ad relevance. His recent work focuses on continuous representations and neural network models, with applications in knowledge base embedding, semantic parsing and question answering. Yih received the best paper award from CoNLL-2011, an outstanding paper award from ACL-2015 and has served as area co-chairs HLT-NAACL-12, ACL-14, EMNLP-16,17,18, program co-chairs CEAS-09, CoNLL-14 and action associated editors TACL, JAIR in recent years. He is also a co-presenter for several tutorials on topics including Semantic Role Labeling NAACL-HLT-06, AAAI-07, Deep Learning for NLP SLT-14, NAACL-HLT-15, IJCAI-16, NLP for Precision Medicine ACL-17, AAAI-18.
Host: Xusen Yin
More Info: http://nlg.isi.edu/nl-seminar/
Webcast: https://bluejeans.com/s/jIoDx/Location: Information Science Institute (ISI) - 6th Floor Conf Rm-CR# 689
WebCast Link: https://bluejeans.com/s/jIoDx/
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://nlg.isi.edu/nl-seminar/
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Sender Decomposition of Cache-Aided Communications and Distributed Computing
Thu, Oct 25, 2018 @ 01:00 PM - 02:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Petros Elia, Communication Systems Department, EURECOM, Sophia Antipolis, France
Talk Title: Sender Decomposition of Cache-Aided Communications and Distributed Computing
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: Recent results have shown that the data-redundancy that can exist in cache-aided communication networks as well as in (coded) distributed computing, can allow for substantial reductions in communication delays. These approaches though face various fundamental challenges that severely reduce the theoretically unbounded gains to much smaller gains. The work here shows a simple way without any additional data exchange between the communicating/computing nodes to decompose the problems of coded caching and coded distributed computing, into problems of smaller dimensionality with much better overall performance. Different manifestations of this "decomposition" phenomenon are explored, each revealing interesting boosts in performance and a direct amelioration of different bottlenecks like the "uneven category bottleneck", the "straggler bottleneck" and the "finite data-set bottleneck".
Biography: Petros Elia received the B.Sc. degree from the Illinois Institute of Technology, and the M.Sc. and Ph.D. degrees in electrical engineering from the University of Southern California in 2001 and 2006 respectively. He is a professor with the Department of Communication Systems at EURECOM, in Sophia Antipolis, France. His latest research deals with information-theoretic aspects of caching, as well with different problems in the area of complexity-constrained communications, coding theory, and surveillance networks. He is a Fulbright scholar, the co-recipient of the NEWCOM++ distinguished achievement award 2008-2011 for a sequence of publications on the topic of complexity in wireless communications, and the recipient of the ERC Consolidator Grant 2017-2022 on cache-aided wireless communications.
Host: Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
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CS Colloquium: Barna Saha (University of Massachusetts Amherst) - Efficient Fine-Grained Algorithms
Fri, Oct 26, 2018 @ 10:00 AM - 11:20 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Barna Saha, University of Massachusetts Amherst
Talk Title: Efficient Fine-Grained Algorithms
Series: Computer Science Colloquium
Abstract: One of the greatest successes of computational complexity theory is the classification of countless fundamental computational problems into polynomial-time and NP-hard ones, two classes that are often referred to as tractable and intractable, respectively. However, this crude distinction of algorithmic efficiency is clearly insufficient when handling today's large scale of data. We need a finer-grained design and analysis of algorithms that pinpoints the exact exponent of polynomial running time, and a better understanding of when a speed-up is not possible. Over the years, many polynomial-time approximation algorithms were devised as an approach to bypass the NP-hardness obstacle of many discrete optimization problems. This area has developed into a rich field producing many algorithmic ideas and has lead to major advances in computational complexity. So far, however, a similar theory for high polynomial time problems to understand the trade-off between quality and running time is vastly lacking.
In this presentation, I will give you an overview of the newly growing field of fine-grained algorithms and complexity, and my contributions therein. This will include fundamental problems such as edit distance computation, all-pairs shortest paths, parsing and matrix multiplication. They have applications ranging from genomics to statistical natural language processing, machine learning and optimization. I will show how as a natural byproduct of improved time complexity, one may design algorithms that are highly parallel as well as streaming algorithms with sublinear space complexity. Finally, motivated by core machine learning applications, I will discuss alternative measures of efficiency that may be equally relevant as time complexity.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Barna Saha is currently an Assistant Professor in the College of Information & Computer Science at the University of Massachusetts Amherst. She is also a Permanent Member of Center for Discrete Mathematics and Theoretical Computer Science (DIMACS) at Rutgers. Before joining UMass in 2014, she was a Research Scientist at AT&T Shannon Laboratories, New Jersey. She spent four wonderful years (2007-2011) at the University of Maryland College Park from where she received her Ph.D. in Computer Science. In Fall 2015, she was at the University of California Berkeley as a Visiting Scholar and as a fellow of the Simons Institute. Her research interests include Theoretical Computer Science, Probabilistic Method & Randomized Algorithms and Large Scale Data Analytics. She is the recipient of NSF CAREER award (2017), Google Faculty Award (2016), Yahoo Academic Career Enhancement Award (2015), Simons-Berkeley Research Fellowship (2015), NSF CRII Award (2015) and Dean's Dissertation Fellowship (2011). She received the best paper award at the Very Large Data Bases Conference (VLDB) 2009 for her work on Probabilistic Databases and was chosen as finalists for best papers at the IEEE Conference on Data Engineering (ICDE) 2012 for developing new techniques to handle low quality data.
Host: David Kempe
Location: Seeley G. Mudd Building (SGM) - 101
Audiences: Everyone Is Invited
Contact: Computer Science Department
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BME seminars
Fri, Oct 26, 2018 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Leo Q. Wan, Ph.D., Associate Professor Department of Biomedical Engineering Rensselaer Polytechnic Institute, Troy, NY
Talk Title: Cellular Asymmetry in Development and Disease
Abstract: Cell Chirality in Development and Disease: Cell chirality (also known as handedness and left-right (LR) asymmetry) is an intrinsic capability of the cell telling left from right. The development of the vertebrate body plan with left-right asymmetry requires the emerging chiral morphogenesis at multicellular levels at specific embryonic stages. Changes in orientation of the LR axis due to genetic or environmental factors can lead to malformations and disease. However, the concept of cell chirality has been recognized, but never studied in detail until the recent development of novel engineering tools. In my lab, we demonstrate that the cultivation of cells on micropatterned 2D surfaces and in 3D graded hydrogels reveals an intrinsic cellular LR asymmetry, which is dependent of cell phenotype and actin cytoskeleton. With these new tools, we examine the role of cell chirality on the development of cardiac LR asymmetry as well as the barrier function of endothelium layers. We find that Protein Kinase C (PKC) activation reverses the inherent chirality from clockwise to counter clockwise in engineering systems. Interestingly, activation of PKC signaling reverses the directional bias of chick cardiac C-looping. Mediating endothelial cell chirality can regulate the permeability of endothelial layers. Overall, our results strongly suggest critical roles of cell chirality in cardiovascular development and disease.
Biography: Dr. Leo Q. Wan is an associate professor in the Department of Biomedical Engineering at the Rensselaer Polytechnic Institute in Troy, NY. His research interests focus on understanding physical biology in tissue development and regeneration, and include Tissue Morphogenesis, Stem Cell Mechanobiology, and Functional Tissue Engineering. He received his Bachelor and Master degrees in Mechanical Engineering from the University of Science and Technology of China. After completing his PhD in Biomedical Engineering at Columbia University in 2007, he became a postdoctoral scientist in the area of Stem Cells and Tissue Engineering. Leo is a Pew scholar (Class 2013), and a recipient of the NIH Director's New Innovator Award, National Science Foundation Early Career Award, American Heart Association Scientist Development Grant, and the March of Dimes Basil O'Connor Starter Scholar Research Award.
Host: Keyue Shen, PhD
More Information: Leo Wan Flier.pdf
Location: 145a
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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W.V.T. RUSCH ENGINEERING HONORS COLLOQUIUM
Fri, Oct 26, 2018 @ 01:00 PM - 01:50 PM
USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. Michael H. Dickinson, California Institute of Technology, Division of Biology and Biological Engineering
Talk Title: Using the Brain of a Modern Fly to Reconstruct the Behaviors of an Ancient Word
Host: EHP and Dr. Prata
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Amanda McCraven
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Mork Family Department of Chemical Engineering and Materials Science Seminar - 11th Annual Spitzer Lecture
Fri, Oct 26, 2018 @ 03:00 PM - 04:00 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Professor Philip Kim, Department of Physics and Applied Physics, Harvard Univer
Talk Title: Stacking Atomic Layers: Quest for New Materials and Physics
Abstract: Modern electronics has been heavily relied on the technology to confine electrons in the interface layers of semiconductors. In recent years, scientists discovered that various atomically thin materials including graphene, a single atomic carbon layer, can be isolated. In these atomically thin materials, quantum physics allows electrons to move only in an effective 2-dimensional (2D) space. By stacking these 2D quantum materials, one can also create atomic-scale heterostructures with a wide variety of electronic and optical properties. I will discuss the creation of new heterostructures based on atomically thin materials and emerging new physics with technological implications therein.
Biography: Professor Philip Kim received his B.S in physics at Seoul National University in 1990 and received his Ph. D. in Applied Physics from Harvard University in 1999. He was Miller Postdoctoral Fellow in Physics from University of California, Berkeley during 1999-2001. In 2002, he joined in Department of Physics at Columbia University as a faculty member. In 2014, he moved to Harvard as Professor of Physics and Professor of Applied Physics. Professor Kim published more than 200 papers in professional journals which are well cited. Many of his papers are published in high impact journals such as Nature, Science and Physical Review Letters. Professor Kim received numerous honors and award including Tomassoni-Chisesi Prizes (2018), Vannevar Bush Faculty Fellowship (2018), Experimental Investigator in Quantum Materials Award, Moore Foundation (2014), Oliver E. Buckley Prize, American Physical Society (2014), IBM Faculty Award (2009), Ho-Am Science Prize (2008); American Physical Society Fellowship (2007), Columbia University Distinguished Faculty Award (2007). In addition, He has given more than 400 invited presentations as keynote speaker, plenary speakers, and invited speakers in international and domestic conferences, colloquiums and department seminars.
Host: Dr. Jayakanth Ravichandran
Location: Seeley G. Mudd Building (SGM) - 123
Audiences: Everyone Is Invited
Contact: Karen Woo/Mork Family
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Seminars in Biomedical Engineering
Mon, Oct 29, 2018 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Joseph Cocozza, PhD, USC, Department of Ophthalmology
Talk Title: New program in biomedical area
Host: Qifa Zhou
Location: Olin Hall of Engineering (OHE) - 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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Fall 2018 Joint CSC@USC/CommNetS-MHI Seminar Series
Mon, Oct 29, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Amir Rahmani, NASA Jet Propulsion Laboratory
Talk Title: Swarm Autonomy and a New Era of Space Exploration
Abstract:
Teams and swarms of autonomous robots and spacecraft hold the promise to change the way some missions are designed and provide new mission opportunities. Monolithic systems can be traded for a swarm of interconnected and coordinating assets. Swarm robotics has reached a level of maturity that can be reliably fielded. NASA's Jet Propulsion Laboratory has long enjoyed leadership in spacecraft formation flying and swarm robotics. This talk will present an overview of JPL's multi-agent autonomy tasks and technologies, including our multi-mission multi-agent autonomy architecture, as well as a number of multi-robot motion-planning tools developed at JPL.
Biography: Dr. Amir Rahmani has a Ph.D. from University of Washington in aeronautics and astronautics and was an assistant professor of aerospace engineering at the University of Miami prior to joining JPL. He has over a decade research experience in distributed space systems, formation flying, as well as swarm robotics. He is the NASA Small Business Technology Transfer (STTR) subtopic manager for coordination and control of swarm of space vehicles.
Host: Mihailo Jovanovic, mihailo@usc.edu
More Info: http://csc.usc.edu/seminars/2018Fall/rahmani.html
More Information: 18.10.29_Amir_Rahmani_NASA_Seminar.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Brienne Moore
Event Link: http://csc.usc.edu/seminars/2018Fall/rahmani.html
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The Best of Both Worlds: Social Agents that Leverage Feelings of Rapport and Anonymity
Mon, Oct 29, 2018 @ 05:00 PM - 06:30 PM
Viterbi School of Engineering Student Organizations
Conferences, Lectures, & Seminars
Speaker: Gale M. Lucas, Research Assistant Professor at USC's ICT
Talk Title: The Best of Both Worlds: Social Agents that Leverage Feelings of Rapport and Anonymity
Series: AAAI@USC Lecture Series
Abstract: This talk presents research comparing social agents to both non-social machines and humans. Social agents have the potential to build rapport like humans (which non-social machines cannot do), but do so while assuring anonymity (which humans cannot do). In this way, they may offer the "best of both worlds" in terms of encouraging users to share personal information and disclose honestly, as well as feel comfortable in situations where they would otherwise be afraid of being negatively evaluated. This has implications for user design and offers possibilities for future research.
Biography: Gale M. Lucas is a Research Assistant Professor at University of Southern California's Institute for Creative Technologies (ICT). After earning her PhD from Northwestern University, she completed her post-doctoral work at ICT, where she established a research program in the areas of Affective Computing and Human-Computer Interaction. Her line of work in affective and personality computing focuses on models predicting mental health, perceptions of trust and emotion in real-world situations. Her work in HCI is centered around understanding how various social factors affect trust in agents and robots.
RSVP: https://goo.gl/forms/uLy23v8sHqz9ZRj72
Host: AAAI at USC
More Info: https://goo.gl/forms/uLy23v8sHqz9ZRj72
Location: John Stauffer Science Lecture Hall (SLH) - 200
Audiences: Everyone Is Invited
Contact: AAAI at USC
Event Link: https://goo.gl/forms/uLy23v8sHqz9ZRj72
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Epstein Institute Seminar - ISE 651
Tue, Oct 30, 2018 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Gino Lim, Professor and Dept. Chair, University of Houston
Talk Title: Drone-aided Healthcare Delivery for Patients with Chronic Diseases in Rural Areas and Uncertain Battery Duration
Host: Professor Julie Higle
More Information: October 30, 2018.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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CS Distinguished Lecture: Nina Balcan (CMU) - Data Driven Algorithm Design
Tue, Oct 30, 2018 @ 03:30 PM - 04:50 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Nina Balcan, Carnegie Mellon University
Talk Title: Data Driven Algorithm Design
Series: Computer Science Distinguished Lecture Series
Abstract: Data driven algorithm design for combinatorial problems is an important aspect of modern data science and algorithm design. Rather than using off the shelf algorithms that only have worst case performance guarantees, practitioners typically optimize over large families of parametrized algorithms and tune the parameters of these algorithms using a training set of problem instances from their domain to determine a configuration with high expected performance over future instances. However, most of this work comes with no performance guarantees. The challenge is that for many combinatorial problems, including partitioning and subset selection problems, a small tweak to the parameters can cause a cascade of changes in the algorithm's behavior, so the algorithm's performance is a discontinuous function of its parameters.
In this talk, I will present new work that helps put data driven combinatorial algorithm selection on firm foundations. We provide strong computational and statistical performance guarantees for several subset selection and combinatorial partitioning problems (including various forms of clustering), both for the batch and online scenarios where a collection of typical problem instances from the given application are presented either all at once or in an online fashion, respectively.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Maria Florina Balcan is an Associate Professor in the School of Computer Science at Carnegie Mellon University. Her main research interests are machine learning, computational aspects in economics and game theory, and algorithms. Her honors include the CMU SCS Distinguished Dissertation Award, an NSF CAREER Award, a Microsoft Faculty Research Fellowship, a Sloan Research Fellowship, and several paper awards. She was a program committee co-chair for the Conference on Learning Theory in 2014 and for the International Conference on Machine Learning in 2016. She is currently board member of the International Machine Learning Society (since 2011), a Tutorial Chair for ICML 2019, and a Workshop Chair for FOCS 2019.
Host: Computer Science Department
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Computer Science Department
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Resilient Distributed Inference in Cyber-Physical Systems
Wed, Oct 31, 2018 @ 12:00 PM - 01:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Soummya Kar, Carnegie Mellon University
Talk Title: Resilient Distributed Inference in Cyber-Physical Systems
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: In applications such as large-scale cyber-physical systems (CPS) and Internet-of-Things (IoT), as the number of devices or agents continues to grow, the integrity and trustworthiness of data generated by these devices becomes a pressing issue of paramount importance. An adversary may hijack individual devices or the communication channel between devices to maliciously alter data streams. In numerous IoT applications, we deploy physical devices throughout an environment, and we are interested in using the stream of sensor measurements to make inferences about the environmental state. Due to the large-scale and distributed nature of devices and data it might be infeasible to carry out computation and decision-making in a classical centralized fashion as well as to prevent attacks and intrusions on all data sources. As a result, reactive countermeasures, such as intrusion detection schemes and resilient inference algorithms become a vital component of security in distributed IoT-type setups.
As an alternative to traditional fusion-center based cloud setups, in this talk we focus on fog-type architectures in which devices themselves perform the necessary computations using local data and peer-to-peer information exchange with neighboring devices to make inferences about an environment. In the first part of the talk, we review distributed inference approaches and algorithms based on the consensus+innovations paradigm. We discuss performance metrics such as rates of convergence, communication complexity, and optimality. The second part of the talk focuses on recent work on secure and resilient variants of these algorithms in adversarial environments. Specifically, focusing on the case of data integrity attacks on the device network, we characterize fundamental trade-offs between resilience, quantified in terms of achievable inference performance and ability to detect intrusions and threats, and model properties such as observability and connectivity of the inter-device communication network.
Biography: Soummya Kar received a B.Tech. in electronics and electrical communication engineering from the Indian Institute of Technology, Kharagpur, India, in May 2005 and a Ph.D. in electrical and computer engineering from Carnegie Mellon University, Pittsburgh, PA, in 2010. From June 2010 to May 2011, he was with the Electrical Engineering Department, Princeton University, Princeton, NJ, USA, as a Postdoctoral Research Associate. He is currently an Associate Professor of Electrical and Computer Engineering at Carnegie Mellon University, Pittsburgh, PA, USA. His research interests include decision-making in large-scale networked systems, stochastic systems, multi-agent systems and data science, with applications to cyber-physical systems and smart energy systems. Recent recognition of his work includes the 2016 O. Hugo Schuck Best Paper Award from the American Automatic Control Council and a 2016 Dean's Early Career Fellowship from CIT, Carnegie Mellon.
Host: Professor Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
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CS Tech Talk: AI for Content Creation and Interaction
Wed, Oct 31, 2018 @ 04:00 PM - 06:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Lei Li & Dr. Jianchao Yang, ByteDance AI Lab
Talk Title: AI for Content Creation and Interaction
Abstract: In the mobile era, we are being presented an exciting opportunity to shape the way people acquire and consume information. In this talk, we will reveal the roles of AI technologies in the information consumption platforms. We will share several recent work at ByteDance AI Lab towards more efficient creation of and interaction with content. We will introduce a robot writer, Xiaomingbot, which has produced more than 60k articles since August 2016, some of them in multiple languages including English, Chinese and Portuguese. It relies on state-of-the-art representation learning for sentences and generative models from data, text, and images. We will also introduce our latest research in visual understanding of objects and scene in short videos, and how these technologies assist authors to create better content. The talk will be accompanied with interactive demos of these technologies in Tiktok(Douyin), Vigo(Huoshan), and Toutiao apps.
Biography: Dr. Lei Li is Director of ByteDance AI Lab. Lei received his B.S. in Computer Science and Engineering from Shanghai Jiao Tong University (ACM class) and Ph.D. in Computer Science from Carnegie Mellon University, respectively. His dissertation work on fast algorithms for mining co-evolving time series was awarded ACM KDD best dissertation (runner up). His recent work on AI writing received 2nd-class award of WU Wenjun AI prize of China. Before Toutiao, he worked at Baidu's Institute of Deep Learning in Silicon Valley as a Principal Research Scientist. Before that, he was working in EECS department of UC Berkeley as a Post-Doctoral Researcher. He has served in the Program Committee for ICML 2014, ECML/PKDD 2014/2015, SDM 2013/2014, IJCAI 2011/2013/2016, KDD 2015/2016, 2017 KDD Cup co-Chair, KDD 2018 hands-on tutorial co-chair, and as a lecturer in 2014 summer school on Probabilistic Programming for Advancing Machine Learning. He has published over 40 technical papers and holds 3 US patents.
Dr. Jianchao Yang is Director of ByteDance AI Lab US. Before joining ByteDance, Jianchao was a manager and principal research scientist at Snap, where he led the computer vision area. He obtained his Ph.D. degree under supervision of Prof. Thomas Huang from University of Illinois at Urbana-Champaign. He has published over 80 technical papers on top conferences and journals, which have attracted over 15k citations from the research community. He is the receipt of Best Student Paper Award in ICCV 2011. He and his collaborators are multiple winners of international competitions and challenges, including PASCAL VOC 2009, ImageNet 2014, WebVision 2017, and NTIRE Super-resolution Challenge 2018.
Host: Xiang Ren
Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 116
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
