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Events for the 4th week of March
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CS Colloquium: Yuanjie Li (UCLA) - Stimulating Intelligence in the Mobile Networked Systems
Mon, Mar 20, 2017 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Yuanjie Li, UCLA
Talk Title: Stimulating Intelligence in the Mobile Networked Systems
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
The mobile networked systems (4G and upcoming 5G) are at a critical stage of the technology revolution. Despite offering working solutions for billions of users, they are complex and closed: The infrastructure lacks guarantees for the right designs and operations, while the mobile client lacks the insights of the "black-box" network behaviors. Both fundamentally limit our understanding of why various problems could happen, and how to resolve them.
In this talk, I describe primitives that stimulate more infrastructure and client intelligence. For the infrastructure, I present verification and state management techniques that enforce provably correct designs and operations. For the client, I show how a data-driven system design allows it to be more active in improving its performance, reliability, and security. These results suggest that the future systems (5G) should be equipped with more intelligence, and make themselves easy to understand and use.
Biography: Yuanjie Li is a Ph.D. candidate in Computer Science at UCLA, advised by Professor Songwu Lu. His interests include the networked systems, mobile computing, and their security. He has won ACM MobiCom'16 Best Community Paper Award and UCLA Dissertation Year Fellowship in 2016. His work has resulted in an open-source community tool (MobileInsight) used by 130 universities and companies so far.
Host: CS Department
Location: Ronald Tutor Hall of Engineering (RTH) - 217
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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AI Seminar
Mon, Mar 20, 2017 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Xiang Ren, Computer Science PhD candidate at University of Illinois at UrbanaChampaign
Talk Title: EFFORT-LIGHT STRUCTMINE: TURNING MASSIVE CORPORA INTO STRUCTURES
Series: Recruitng Seminar
Abstract: The realworld 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 a data-driven framework, EffortLight StructMine, that extracts structured facts from massive corpora without explicit human labeling effort. In particular, I will discuss how to solve three structure mining tasks under Effort-Light StructMine framework: from identifying typed entities in text, to fine-grained entity typing, to extracting typed relationships between entities. Together, these three solutions form a clear roadmap for turning a massive corpus into a structured network to represent its factual knowledge. Finally, I will share some directions towards mining corpus-specific structured networks for knowledge discovery.
Biography: Xiang Ren is a Computer Science PhD candidate at University of Illinois at Urbana-Champaign, working with Jiawei Han and the Data and Information System DAIS Research Lab. The research Xiang develops data-driven methods for turning unstructured text data into machine-actionable structures. More broadly, his research interests span data mining, machine learning, and natural language processing, with a focus on making sense of massive text corpora. His research has been recognized with several prestigious awards including a Google PhD Fellowship, a Yahoo!-DAIS Research Excellence Award, and a C. W. Gear Outstanding Graduate Student Award from UIUC Computer Science. Technologies he developed has been transferred to US Army Research Lab, NIH, Microsoft, Yelp and TripAdvisor
Host: Craig Knoblock
Webcast: http://webcastermshd.isi.edu/Mediasite/Play/6b83d48fc61f4e398d8d8bbdff0004e01dLocation: Information Science Institute (ISI) - 11th Floor Large CR #1135
WebCast Link: http://webcastermshd.isi.edu/Mediasite/Play/6b83d48fc61f4e398d8d8bbdff0004e01d
Audiences: Everyone Is Invited
Contact: Alma Nava / Information Sciences Institute
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Seminars in Biomedical Engineering
Mon, Mar 20, 2017 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Zhongping Chen , Professor of Biomedical Engineering, UC Irvine, Beckman Laser Institute
Talk Title: Novel OCT for Biomedical Application
Host: Qifa Zhou
Location: Olin Hall of Engineering (OHE) - 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute for Electrical Engineering Joint Seminar Series on Cyber-Physical Systems
Mon, Mar 20, 2017 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Brian Munsky, Assistant Professor, Colorado State University
Talk Title: Identification of stochastic models to predict single-cell gene regulation dynamics
Abstract: Stochastic fluctuations can cause identical cells or individual molecules to exhibit wildly different behaviors. Often labeled "noise," these fluctuations are frequently considered a nuisance that compromises cellular responses, complicates modeling, makes predictive understanding and control all but impossible. However, if we computationally examine fluctuations more closely and carefully match them to discrete stochastic analyses, we discover virtually untapped, yet powerful sources of information and new opportunities. In this talk, I will present our collaborative endeavors to integrate single-cell and single-molecule experiments with precise stochastic analyses to gain new insight and quantitatively predictive understanding for signal-activated gene regulation. I will explain how we experimentally quantify transcription dynamics at high temporal and spatial resolutions; how we use precise computational analyses to model this data and efficiently infer biological mechanisms and parameters; how we predict and evaluate the extent to which model constraints (i.e., data) and uncertainty (i.e., model complexity) contribute to our understanding. We will examine how different data statistics (e.g., expectation values versus probability densities) contribute to model bias and uncertainty, and we will show how these affect predictive power. Finally, we will introduce a new approach to compute the Fisher Information Matrix, and we will illustrate its application for the improved design of single-cell experiments.
Biography: Dr. Munsky received B.S. and M.S. degrees in Aerospace Engineering from the Pennsylvania State University in 2000 and 2002, respectively, and his Ph.D. in Mechanical Engineering from the University of California at Santa Barbara in 2008. Following his graduate studies, Dr. Munsky worked at the Los Alamos National Laboratory -” as a Director's Postdoctoral Fellow (2008-2010), as a Richard P. Feynman Distinguished Postdoctoral Fellow in Theory and Computing (2010-2013), and as a Staff Scientist (2013). In 2014, he joined the Colorado State University Department of Chemical and Biological Engineering and the School of Biomedical Engineering, in which he is now an Assistant Professor. Dr. Munsky is best known for his discovery of Finite State Projection algorithm, which has enabled the efficient study of probability distribution dynamics for stochastic gene regulatory networks. Dr. Munsky's research interests are in the integration of discrete stochastic models with single-cell experiments to identify predictive models of gene regulatory systems. Dr. Munsky was the recipient of the 2008 UCSB Department of Mechanical Engineering best Ph.D. Dissertation award, the 2010 Leon Heller Postdoctoral Publication Prize, and the 2012 LANL Postdoc Distinguished Performance Award for his work in this topic. Dr. Munsky became a Keck Scholar in 2016. Dr. Munsky is the contact organizer of the internationally recognized, NIH-funded q-bio Summer School (q-bio.org), where he runs a course on single-cell stochastic gene regulation.
Host: Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Estela Lopez
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USC Stem Cell Seminar: Flora Vaccarino, Yale University
Tue, Mar 21, 2017 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Flora Vaccarino, Yale University
Talk Title: TBD
Series: Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research at USC Distinguished Speakers Series
Host: USC Stem Cell
More Info: http://stemcell.usc.edu/events
Webcast: http://keckmedia.usc.edu/stem-cell-seminarWebCast Link: http://keckmedia.usc.edu/stem-cell-seminar
Audiences: Everyone Is Invited
Contact: Cristy Lytal/USC Stem Cell
Event Link: http://stemcell.usc.edu/events
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CS Colloquium: Justin Cheng (Stanford) - Antisocial Computing: Explaining and Predicting Negative Behavior Online
Tue, Mar 21, 2017 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Justin Cheng, Stanford University
Talk Title: Antisocial Computing: Explaining and Predicting Negative Behavior Online
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
Antisocial behavior and misinformation are increasingly prevalent online. As users interact with one another on social platforms, negative interactions can cascade, resulting in complex changes in behavior that are difficult to predict. My research introduces computational methods for explaining the causes of such negative behavior and for predicting its spread in online communities. It complements data mining with crowdsourcing, which enables both large-scale analysis that is ecologically valid and experiments that establish causality. First, in contrast to past literature which has characterized trolling as confined to a vocal, antisocial minority, I instead demonstrate that ordinary individuals, under the right circumstances, can become trolls, and that this behavior can percolate and escalate through a community. Second, despite prior work arguing that such behavioral and informational cascades are fundamentally unpredictable, I demonstrate how their future growth can be reliably predicted. Through revealing the mechanisms of antisocial behavior online, my work explores a future where systems can better mediate interpersonal interactions and instead promote the spread of positive norms in communities.
Biography: Justin Cheng is a PhD candidate in the Computer Science Department at Stanford University, where he is advised by Jure Leskovec and Michael Bernstein. His research lies at the intersection of data science and human-computer interaction, and focuses on cascading behavior in social networks. This work has received a best paper award, as well as several best paper nominations at CHI, CSCW, and ICWSM. He is also a recipient of a Microsoft Research PhD Fellowship and a Stanford Graduate Fellowship.
Host: CS Department
Location: Ronald Tutor Hall of Engineering (RTH) - 217
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Improved Myocardial Arterial Spin Labeled Perfusion Imaging
Tue, Mar 21, 2017 @ 01:00 PM - 02:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Hung Phi Do, Department of Physics and Astronomy, University of Southern California
Talk Title: Improved Myocardial Arterial Spin Labeled Perfusion Imaging
Series: Medical Imaging Seminar Series
Abstract: Coronary artery disease (CAD) affects more than 15.5 million Americans and causes approximately 310,000 deaths per year. Several different diagnostic tests are performed to diagnose and manage this disease. One of the most common is perfusion stress testing, primarily performed using single photon emission computed tomography (SPECT) or first-pass cardiovascular magnetic resonance (CMR). These methods require the use of ionizing radiation or exogenous contrast agents that carry associated risks to patients, especially those who require frequent assessment or have kidney dysfunction. Myocardial arterial spin labeling (ASL) is a promising MRI-based perfusion imaging method that can quantitatively measure myocardial tissue perfusion without the use of ionizing radiation or exogenous contrast agents. Its feasibility has been previously demonstrated by our lab, however several challenges remain, including low sensitivity, coarse spatial resolution, and limited spatial coverage. The contributions of this dissertation are (1) improving sensitivity, (2) exploring clinical applications, and (3) developing a new and advantageous labeling method for myocardial ASL.
Biography: Hung Phi Do is a Physics Ph.D. student working under the supervision of Prof. Nayak at the Magnetic Resonance Engineering Laboratory. His research focuses are MR physics and MR pulse sequence development for quantitative cardiovascular magnetic resonance. He received an M.S. in Electrical Engineering from the University of Southern California in 2014, a Diploma in Physics from the International Center for Theoretical Physics in 2009, and a B.S. in Physics from the Hanoi National University of Education in 2007.
Host: Prof. Krishna Nayak
Location: Hughes Aircraft Electrical Engineering Center (EEB) - PHE223
Audiences: Everyone Is Invited
Contact: Talyia White
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MHI Seminar Series - Visitor Program
Tue, Mar 21, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Magnús Már Halldórsson, Professor at Reykjavik University's School of Computer Science
Talk Title: Algorithms and Models for the Capacity of Arbitrary Wireless Networks
Abstract: At the heart of wireless network operation is the fundamental question of their capacity: How much communication can be achieved in a network, utilizing all the tools and diversity available: power control, scheduling, routing, channel assignment and rate adjustment?
The obvious aims of obtaining general purpose algorithms to solve this question run into two (walls) challenges:
- How to model communication and interference faithfully, and
- How to reason algorithmically in the more accurate models, which are also more intricate and harder to analyze.
We overview recent progress in developing algorithms for capacity and scheduling in the physical (or SINR) model with good performance guarantees on arbitrary networks. In particular, we indicate how many of the complications of the physical models can be abstracted away, at a small cost in performance. We also outline various efforts to add additional realism to the models, while maintaining generality and algorithmic tractability. We conclude with open questions and challenges.
This is based on joint work with Tigran Tonoyan
Biography: Prof. Magnús Már Halldórsson from Reyjkjavik University in Iceland will visit USC in late March 2017. He is a leading expert in algorithms for distributed computing and wireless networks. He has been the Chair of top conferences in the area including PODC 2014 and ICALP 2015. In 2017 he is leading the organization a Dagstuhl conference on "Foundations of Wireless Networking" together with Profs. C. Fragouli (UCLA), K. Jamieson (Princeton) and B. Krishnamachari (USC).
Host: Bhaskar Krishnamachari
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Cathy
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CS Colloquium: Nihar Shah (UC Berkeley) - Learning from People
Tue, Mar 21, 2017 @ 04:00 PM - 05:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Nihar Shah, UC Berkeley
Talk Title: Learning from People
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
Learning from people represents a new and expanding frontier for data science. Two critical challenges in this domain are of developing algorithms for robust learning and designing incentive mechanisms for eliciting high-quality data. In this talk, I describe progress on these challenges in the context of two canonical settings, namely those of ranking and classification. In addressing the first challenge, I introduce a class of "permutation-based" models that are considerably richer than classical models, and present algorithms for estimation that are both rate-optimal and significantly more robust than prior state-of-the-art methods. I also discuss how these estimators automatically adapt and are simultaneously also rate-optimal over the classical models, thereby enjoying a surprising a win-win in the bias-variance tradeoff. As for the second challenge, I present a class of "multiplicative" incentive mechanisms, and show that they are the unique mechanisms that can guarantee honest responses. Extensive experiments on a popular crowdsourcing platform reveal that the theoretical guarantees of robustness and efficiency indeed translate to practice, yielding several-fold improvements over prior art.
Biography: Nihar B. Shah is a PhD candidate in the EECS department at the University of California, Berkeley. He is the recipient of the Microsoft Research PhD Fellowship 2014-16, the Berkeley Fellowship 2011-13, the IEEE Data Storage Best Paper and Best Student Paper Awards for the years 2011/2012, and the SVC Aiya Medal from the Indian Institute of Science for the best master's thesis in the department. His research interests include statistics and machine learning, with a current focus on applications to learning from people.
Host: CS Department
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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MHI CommNetS
Wed, Mar 22, 2017 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Corey Baker, UC San Diego
Talk Title: When Disaster Strikes: Supplementing Centralized Infrastructure with Opportunistic Communication
Series: CommNetS
Abstract: Reliance on Internet connectivity is detrimental where modern networking technology is lacking, power outages are frequent, or network connectivity is sparse or non-existent (i.e., developing countries, natural disasters, and in-field military scenarios). Realization of the limitations resulting from reliance on Internet and cellular connectivity were prevalent in Hurricane Matthew (2016), which killed over 1000 people and destroyed cellular infrastructure. As an alternative, deploying resilient networking technology can facilitate the flow of information in resource-deprived environments to disseminate life saving data. In addition, leveraging opportunistic communication can supplement cellular networks to assist with keeping communication channels open during high-use and extreme situations. This talk will discuss the progress of a research platform and middleware that enables opportunistic communication and in vivo evaluation of delay tolerant routing schemes when the Internet is interrupted or unavailable by leveraging node relationships to create a delay tolerant social network. The solutions discussed in this talk further include applications related to IoT, mobile healthcare, and smart city environments.
Biography: Corey E. Baker, Ph.D., is a University of California President's Postdoctoral Fellow in the Electrical and Computer Engineering Department at the University of California, San Diego and is mentored by Professor Ramesh Rao. Dr. Baker's research interests are in the area of cyber physical systems specializing in opportunistic wireless communication for the Internet of Things (IoT), smart cities, smart homes, and mobile health environments. Particularly, Dr. Baker is interested in pragmatic applications and the fundamental issues related to real-world resource availability in today's operating systems for opportunistic wireless communication. Dr. Baker received a B.S. degree in Computer Engineering from San Jose State University, a M.S. in Electrical and Computer Engineering from California State University, Los Angeles, and M.S. and Ph.D. degrees in Electrical and Computer Engineering from the University of Florida where he was advised by Professor Janise McNair. Corey has served on the board of directors of the National Society of Black Engineers (NSBE) numerous times as a two term National Treasurer and CFO, two term National Treasurer Emeritus, and as the Region 6 Chairperson. Dr. Baker is currently a NSBE Region 6 Finance Zone Advisor. Formerly, Dr. Baker was the official blogger for GEM and blogged about topics to promote success amongst STEM graduate students which included securing graduate school funding, navigating Ph.D. programs, and publishing.
Host: Prof. Ashutosh Nayyar
Location: 248
Audiences: Everyone Is Invited
Contact: Annie Yu
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Neuro-Gastroenterologic Engineering
Wed, Mar 22, 2017 @ 10:45 AM - 11:45 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Todd P. Coleman, Associate Professor/UCSD
Talk Title: Neuro-Gastroenterologic Engineering
Abstract: The discoordination between the central and autonomic nervous systems is increasingly being identified as playing a key role in affecting neurological, psychiatric, and gastroenterologic problems; the causal role that the enteric nervous system may play in Parkinson's disease serves as an example. However, traditionally, the brain and GI system have been studied scientifically and treated clinically, separately. There is a dearth of approaches to use engineering perspectives to better measure, characterize, and provide actionable insight about the GI system as well as its interplay with the brain. In this talk, we will discuss our recent contributions to address this unmet need. Specifically, we will discuss our recent development of novel methods to assess the GI system with high-resolution multi-electrode surface potential recordings, an approach that non-invasively characterizes propagation velocity and propagation patterns consistent with gastric serosal slow wave myoelectric activity, which had not been accomplished until now. We will also highlight novel applied probability methods to interpret these classes of dynamic multi-channel physiologic datasets, including directed information graphs, a new class of probabilistic graphical models that provides minimal descriptions of causal relationships in multiple time series. To enable the recording of multiple physiologic time series simultaneously and unobtrusively, we will lastly discuss our development of multi-electrode arrays embedded within skin-mounted adhesives for ambulatory monitoring. We will highlight how all of these methods and technologies are being used within the context of neuro-gastroenterologic engineering and how there is transformational potential to improve health, reduce healthcare costs, and advance science.
Biography: Todd P. Coleman received B.S. degrees in electrical engineering (summa cum laude), as well as computer engineering (summa cum laude) from the University of Michigan. He received M.S. and Ph.D. degrees from MIT in electrical engineering, and did postdoctoral studies at MIT in neuroscience. He is currently an Associate Professor in Bioengineering at UCSD, where he directs the Neural Interaction Laboratory. Dr. Coleman's research has been featured on CNN, BBC, and the New York Times. Dr. Coleman has been selected as a National Academy of Engineering Gilbreth Lecturer and a TEDMED speaker.
Host: Dr. Sandeep Gupta
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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Computer Science General Faculty Meeting
Wed, Mar 22, 2017 @ 12:00 PM - 02:00 PM
Thomas Lord Department of Computer Science
Receptions & Special Events
Bi-Weekly regular faculty meeting for invited full-time Computer Science faculty only. Event details emailed directly to attendees.
Location: Ronald Tutor Hall of Engineering (RTH) - 526
Audiences: Invited Faculty Only
Contact: Assistant to CS chair
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Seminar Announcement: Soft Robots for Delicate and Effective Interactions with Humans: Multi-Scale Soft Biomedical Robots
Wed, Mar 22, 2017 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Tomasso Ranzani, Postdoctoral Fellow, Harvard University
Talk Title: Soft Robots for Delicate and Effective Interactions with Humans: Multi-Scale Soft Biomedical Robots
Abstract: Soft robots are constructed from compliant materials, resulting in machines that can safely interact with the natural environments. Given their inherent compliance, they are particularly suitable for exploring and interacting with unstructured environments, and manipulating soft, delicate, and irregular objects. These properties make soft robots particularly promising for biomedical applications, such as wearable and medical devices, given the highly compliant and delicate structures of the body. On the other hand, the compliance of soft robots limits their ability to effectively apply forces on objects whose stiffness is comparable to the one of the robot itself, leading to the challenge of matching the compliance of soft devices with the environment or objects they will encounter. During this talk, I will describe progress in soft robotics and its potential for revolutionizing biomedical devices. I will introduce a soft manipulator inspired by the structure and the manipulation capabilities of the octopus tentacle, which is able to selectively tune its stiffness to address the challenge of impedance matching. I will also introduce the potential of soft robotics at the millimeter and micrometer scales, addressing the challenge of manufacturing complex meso-scale three-dimensional soft structures using two-dimensional processes involving laser machining, lamination, and soft lithography. These manufacturing processes could pave the way for soft microrobots as well as a new class of deployable, small, and safe medical devices.
Biography: Tommaso Ranzani received the Master's degree in biomedical engineering from the University of Pisa, Pisa, Italy, in 2010 and the Ph.D. degree in BioRobotics in 2014 at the BioRobotics Institute, Scuola Superiore Sant'Anna, Pontedera, Italy. During his Ph.D., he explored soft robotic technologies to develop a bioinspired manipulator, which integrates design principles from biological systems for performing advanced procedures in minimally invasive surgery. He is currently a postdoctoral fellow at the Harvard Microrobotics Laboratory and at the Harvard Biodesign Laboratory working on different manufacturing paradigms, materials, and actuation technologies to develop novel mm-scale robotic tools and structures able to overcome current challenges in medicine and surgery. His research interests include soft and bioinspired robotics, medical robotics and advanced manufacturing.
Host: Department of Aerospace and Mechanical Engineering
More Info: http://ame-www.usc.edu/seminars/3-22-17-ranzani.shtml
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Ashleen Knutsen
Event Link: http://ame-www.usc.edu/seminars/3-22-17-ranzani.shtml
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Film Screening of She Started It - featuring BS Computer Science Alumna
Wed, Mar 22, 2017 @ 07:00 PM - 10:00 PM
Thomas Lord Department of Computer Science
Receptions & Special Events
The Computer Science Department and USC School of Cinema are pleased to bring you a special screening of She Started It.
RSVP via: http://cinema.usc.edu/SheStartedIt
She Started It gives a new face to the popular image of the tech entrepreneur: a female face.
Following five women over two years as they pitch VCs, build teams, bring products to market, fail and start again, She Started It takes viewers on a global roller coaster ride from San Francisco to Mississippi, France and Vietnam. Along the way, it weaves in big-picture perspectives from women like investor Joanne Wilson; White House CTO Megan Smith; GoldieBlox CEO Debbie Sterling; and Ruchi Sanghvi, the first female engineer at Facebook.
Through intimate, action-driven storytelling, She Started It explores the cultural roots of female underrepresentation in entrepreneurship. including pervasive self-doubt, fear of failure, and risk aversion among young women. It exposes, too, the structural realities women face as they become entrepreneurs, including lack of female role models and investors, and the persistent dearth of venture capital funding made available to women-led companies.
Directed by Nora Poggi
Co-Directed by Insiyah Saeed
Produced by Nora Poggi and Insiyah Saeed
Followed by a Q&A with Nora Poggi and USC B.S. Computer Science 2009 Alumna Thuy Truong
7:00 P.M. on Wednesday, March 22nd, 2017
The Ray Stark Family Theatre, SCA 108
900 W. 34th Street, Los Angeles, CA 90007
FREE ADMISSION. OPEN TO THE PUBLIC. RSVPs REQUIRED.
RSVP via: http://cinema.usc.edu/SheStartedIt
Location: School Of Cinematic Arts (SCA) - 108
Audiences: Everyone Is Invited
Contact: Ryan Rozan
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CS Colloquium: Long Lu (Stony Brook University) - New OS and Programming Support for Securing Mobile and IoT Platforms
Thu, Mar 23, 2017 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Long Lu, Stony Brook University
Talk Title: New OS and Programming Support for Securing Mobile and IoT Platforms
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
Software running on mobile and IoT platforms increasingly falls victim to new attacks, which cause device compromises and privacy leaks that are often more severe than their counterparts on conventional computers. My research finds that new attacks on these platforms are possible primarily due to a gap between the evolving security needs of software and the legacy security support provided by operating systems and programming tools.
In this talk, I will first overview my recent works that aim to bridge this gap by rethinking the principles and designs of security mechanisms in operating systems, compilation toolchains, and TEEs (Trusted Execution Environments). I will then present two systems that address a critical yet previously unmet security need of today's apps, namely in-app isolation. The first system introduces a new OS-managed code execution unit, called shred, to compensate thread and process. A shred is a segment of a thread execution. Code inside a shred can access, in addition to the regular virtual memory, a private memory region. Using shreds, programmers can now protect sensitive in-memory code and data against untrusted code running in the same process or thread. The second system enables comprehensive security policy enforcement at the sub-app granularities, preventing mutually distrusting app modules from abusing each other's resources and privileges. In the final part of the talk, I will discuss my ongoing and future works on laying the system foundation for securing IoT platforms.
Biography: Long Lu is an Assistant Professor of Computer Science and the director of RiS3 Lab at Stony Brook University. Long's research spans the broad area of systems and software security. His recent work is focused on application and operating system security for emerging platforms, such as mobile and IoT/CPS devices. He designs code and data protection mechanisms, program analysis techniques, and user-facing software tools to prevent real attacks. He constantly publishes in the top-tier computer security conferences and is frequently invited to serve on their program committees. His research outcomes have been adopted by IBM, Microsoft, NEC, and Samsung. His work is currently funded by NSF, ONR, ARO, and AFRL. Long is a recipient of the NSF CAREER Award and the Air Force Faculty Fellowship. He holds a Ph.D. in Computer Science from Georgia Tech.
Host: CS Department
Location: Ronald Tutor Hall of Engineering (RTH) - 217
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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CS Colloquium: Matthew Brown (UCLA) -Typed Self-Applicable Meta-Programming
Thu, Mar 23, 2017 @ 04:00 PM - 05:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Matthew Brown, UCLA
Talk Title: Typed Self-Applicable Meta-Programming
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
Meta-programming is a fundamental technique in computer science. It allows high levels of abstraction to be utilized with low cost. Meta-programs like compilers, interpreters, and program optimizers make high-level programming languages efficient, providing increased programmer productivity and performance comparable to lower-level languages. Self-applicable meta-programming makes meta-programming first-class, enabling many powerful
techniques. However, meta-programming and particularly self-applicable meta-programming is often complex, error-prone and difficult to debug. For these reasons it has untapped potential to provide benefits in many areas. Typed meta-programming uses modern techniques for type checking meta-programs to make them less error-prone and easier to understand and debug. It also brings the power of self-applicable meta-programming to statically-typed languages, ending a long-persisting trade-off between static and dynamic type checking. In this talk I discuss foundational results in typed self-applicable meta-programming.
Biography: Matt Brown is PhD candidate at UCLA, working in the compilers lab under Jens Palsberg. He holds a Bachelor's degree from UC Santa Cruz and a Master's from UCLA. His research focus is typed self-applicable meta-programming, which uses typed program representation techniques to ensure correctness properties of self-applicable meta-programs like self-interpreters. Other research interests include type systems, program verification, concurrency, and functional programming languages. He was recently a part-time lecturer at Loyola Marymount University and has six years of industry experience.
Host: CS Department
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Civil and Environmental Engineering Seminar
Fri, Mar 24, 2017 @ 11:00 AM - 12:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Susan Hubbard, University of California, Berkeley
Talk Title: Geophysical Approaches for Quantifying Watershed Structure and Function
Host: Dr. Felipe de Barros
More Information: Hubbard Seminar Announcement.pdf
Location: 102
Audiences: Everyone Is Invited
Contact: Kaela Berry
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AI Seminar: EVOLUTION OF NEURAL NETWORKS
Fri, Mar 24, 2017 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Risto Miikkulainen, Univ. of Texas
Talk Title: EVOLUTION OF NEURAL NETWORKS
Series: Artificial Intelligence Seminar
Abstract: Evolution of artificial neural networks has recently emerged as a powerful technique both in deep networks and reinforcementlearning. While the performance of deep learning networks depends crucially on the network architecture; with neuroevolution, it ispossible to discover such architectures automatically. While reinforcement learning works well when the environment is fully observable, neuroevolution makes it possible to disambiguate hidden state through memory. In this tutorial, I will review 1 neuroevolution methods that evolve fixed-topology networks, network topologies, and network construction processes, 2 ways of combining gradient-based training with evolutionary methods, and 3 applications of neuroevolution to control, robotics, artificial life, and games.
Biography: Risto Miikkulainen is a Professor of Computer Science at the University of Texas at Austin and a Research Fellow at Sentient Technologies, Inc. He received an M.S. in Engineering from the Helsinki University of Technology, Finland, in 1986, and a Ph.D. in Computer Science from UCLA in 1990. His current research focuses on methods and applications of neuroevolution, as well as neural network models of natural language processing, and self-organization of the visual cortex; he is an author of over 370 articles in these research areas. He is an IEEE Fellow, member of the Board of Governors of the Neural Network Society, and an action editor of Cognitive Systems Research and IEEE Transactions on Computational Intelligence and AI in Games.
Host: Mayank Kejriwal
Webcast: http://webcastermshd.isi.edu/Mediasite/Play/f0024e2d2140457586ec2ed6a78026b01dLocation: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, Marina Del Rey
WebCast Link: http://webcastermshd.isi.edu/Mediasite/Play/f0024e2d2140457586ec2ed6a78026b01d
Audiences: Everyone Is Invited
Contact: Peter Zamar
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W.V.T. Rusch Engineering Honors Program Colloquium
Fri, Mar 24, 2017 @ 01:00 PM - 01:50 PM
USC Viterbi School of Engineering, Viterbi School of Engineering Student Affairs
University Calendar
Join us for a presentation by Dr. Vikram Ravi, Millikan Fellow in Astronomy, Cahill Center for Astronomy and Physics at the California Institute of Technology, titled "The Hottest Explosions of the Universe."
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Ramon Borunda/Academic Services
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Seminars in Biomedical Engineering
Fri, Mar 24, 2017 @ 02:30 PM - 04:30 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Aditya Rajagopal, PhD, Founder & CTO, Chromacode; Visiting Associate (Visiting Faculty), Caltech
Talk Title: Engineering Methods for Biological Measurement
Series: Seminars in BME (Lab Rotations)
Host: Brent Liu, PhD
Location: Corwin D. Denney Research Center (DRB) - 146
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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Ming Hsieh Institute Seminar Series on Integrated Systems
Fri, Mar 24, 2017 @ 02:30 PM - 04:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Aydin Babakhani, Assistant Professor, Rice University
Talk Title: Silicon-based Integrated Sensors and Systems with On-chip Antennas From Picosecond Pulse Radiators to Miniaturized Spectrometers
Host: Profs. Hossein Hashemi, Mike Chen, Dina El-Damak, and Mahta Moghaddam
More Information: MHI Seminar Series IS - Aydin Babakhani.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Jenny Lin
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NL Seminar - Intuitive Interactions with Black-box Machine Learning
Fri, Mar 24, 2017 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Sameer Singh, UCI
Talk Title: Intuitive Interactions with Black-box Machine Learning
Series: Natural Language Seminar
Abstract: Machine learning is at the forefront of many recent advances in natural language processing, enabled in part by the sophisticated models and algorithms that have been recently introduced. However, as a consequence of this complexity, machine learning essentially acts as a black-box as far as users are concerned. It is incredibly difficult to understand, predict, or "fix" the behavior of NLP models that have been deployed. In this talk, I propose interpretable representations that allow users and machine learning models to interact with each other: enabling machine learning models to provided explanations as to why a specific prediction was made and enabling users to inject domain knowledge into machine learning. The first part of the talk introduces an approach to estimate local, interpretable explanations for black-box classifiers and describes an approach to summarize the behavior of the classifier by selecting which explanations to show to the user. I will also briefly describe work on "closing the loop", i.e. allowing users to provide feedback on the explanations to improve the model, for the task of relation extraction, an important subtask of natural language processing. In particular, we introduce approaches to both explain the relation extractor using logical statements and to inject symbolic domain knowledge into relational embeddings to improve the predictions. I present experiments to demonstrate that an interactive interface is effective in providing users an understanding of, and an ability to improve, complex black-box machine learning systems.
Biography: Sameer Singh is an Assistant Professor of Computer Science at the University of California, Irvine. He is working on large-scale and interactive machine learning applied to information extraction and natural language processing. Till recently, Sameer was a Postdoctoral Research Associate at the University of Washington. He received his PhD from the University of Massachusetts, Amherst in 2014, during which he also interned at Microsoft Research, Google Research, and Yahoo! Labs on massive-scale machine learning. He was selected as a DARPA Riser, was awarded the Adobe Research Data Science Award, won the grand prize in the Yelp dataset challenge, has been awarded the Yahoo! Key Scientific Challenges fellowship, and was a finalist for the Facebook PhD fellowship. Sameer has published more than 30 peer-reviewed papers at top-tier machine learning and natural language processing conferences and workshops.
Host: Marjan Ghazvininejad and Kevin Knight
More Info: http://nlg.isi.edu/nl-seminar/
Location: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, Marina Del Rey
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://nlg.isi.edu/nl-seminar/
