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Conferences, Lectures, & Seminars
Events for March
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W.V.T. RUSCH ENGINEERING HONORS COLLOQUIUM
Fri, Mar 01, 2019 @ 01:00 PM - 01:50 PM
USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Speaker: Mr. Mark Navarrete, Structures Design Manager, Northrop Grumman Corporation
Talk Title: Structural Design Engineering in The Aerospace Industry
Host: EHP and Dr. Prata
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Amanda McCraven
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Civil and Environmental Engineering Seminar
Fri, Mar 01, 2019 @ 01:00 PM - 02:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Zahra Kharal, University of Toronto
Talk Title: Towards Understanding the Seismic Behaviour of FRP Confined Concrete Columns
Abstract: A large inventory of deficient reinforced concrete (RC) structures exist in which steel corrosion is the main cause of deficiency. Corrosion of steel in columns is especially a serious issue in existing structures, as it can lead to unexpected brittle structural failure in earthquakes or worse, under static gravity loads alone. While upgrading of these structures is a priority, the new structures need to be built such that they do not undergo similar ageing problems. Research on glass fibre reinforced polymers (GFRP) as internal reinforcement has shown promise as a durable material for building sustainable infrastructure. The research that I will present investigated the use of GFRP longitudinal bars and GFRP transverse reinforcement in columns for seismic resistance. The experimental program involved extensive testing of full-scale GFRP- and steel-RC columns under simulated earthquake loads. The variables investigated included column shape (circular or square), amount and spacing of transverse reinforcement, type of longitudinal and transverse reinforcement (steel or GFRP), reinforcement configuration and axial load level. A significant conclusion drawn from this research was that not only can GFRP be used as primary transverse reinforcement in columns but, in some cases, can provide better confinement than steel. In addition, a computation program was developed that can predict the behavior of steel and FRP-spiral and -tied confined columns subjected to seismic loading. The novelty of this program is in being able to rapidly analyze the column while still capturing the full nonlinear response of the column.
Host: Sonny Astani Department of Civil and Environmental Engineering
Location: Ray R. Irani Hall (RRI) - 101
Audiences: Everyone Is Invited
Contact: Salina Palacios
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Clarice Aiello - Seminar, Friday, March 1st at 2pm in EEB 132
Fri, Mar 01, 2019 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Clarice Aiello, Stanford University
Talk Title: From nanotech to living sensors: unraveling the spin physics of biosensing at the nanoscale
Abstract: I am a quantum engineer interested in how quantum physics informs biology at the nanoscale.
As a physicist, I have developed high-performance nanosensors that essentially worked due to room-temperature quantum effects in noisy environments. Currently, I am focusing on "living sensors" -- organisms and cells that respond to minute stimuli, routinely outperforming technological probes in awe-inspiring ways. Unveiling and controlling the underlying physical mechanisms employed by "living sensors" impact: the engineering of ultrasensitive, bio-inspired electromagnetic probes; the elucidation of mesmerizing natural feats such as animal navigation; and the advancement of therapeutics for metabolic-related diseases.
Substantial in vitro and physiological experimental results are consistent with the fact that similar spin physics might underlie biosensing modalities as varied as organismal magnetic field detection and metabolic regulation of oxidative stress in cells.
Can spin physics be established -- or refuted! -- to account for physiologically relevant biosensing phenomena, and be manipulated to technological and therapeutical advantage? This is the broad, exciting question that I wish to address in my scientific career.
Biography: Clarice D. Aiello is a quantum engineer born and raised in Brazil. She trained as an experimental physicist in Europe, having earned a Diplome d'Ingenieur de l'Ecole Polytechnique in France, and an M.Phil. from the University of Cambridge, Trinity College, in England.
Research brought Clarice to the American shore. She completed her Ph.D. in Electrical Engineering at MIT with Prof. Paola Cappellaro. Her work has been funded by sources as diverse as the Fulbright Commission, the Schlumberger Foundation and UNESCO. Clarice is also a recipient of MIT's School of Engineering's "Graduate Student Award for Extraordinary Teaching and Mentoring".
Clarice then undertook postdoctoral research with Prof. Naomi Ginsberg, in the Chemistry Department of the University of California at Berkeley. Currently, Clarice is a Life Sciences Research Foundation/Moore Foundation postdoctoral fellow with Prof. Manu Prakash, in Stanford University's Bioengineering Department.
She has recently been chosen as a "Rising Star in Physics", and intends to invest her interdisciplinary training to investigate how quantum physics informs biology at the nanoscale.
Host: ECE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Satellite Propulsion SystemsSat, Mar 02, 2019 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Abstract: The Satellite Propulsion Systems program provides an understanding of the basic principles and figures of merit of Rocket Propulsion. Upon completion of the 4-day program, participants will be able to apply these principles to spacecraft propulsion system and components Analysis-&-Design, Testing, Ground Operations, Flight Operations, and End-of-life (EOL) De-orbit.
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/astronautical-engineering/satellite-propulsion-systems/
Audiences: Registered Attendees
Contact: Corporate & Professional Programs
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CS Colloquium: Rahul Chatterjee (Cornell University) - Empiricism-Informed Secure System Design: From Improving Passwords to Helping Domestic Violence Victims
Mon, Mar 04, 2019 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Rahul Chatterjee, Cornell University
Talk Title: Empiricism-Informed Secure System Design: From Improving Passwords to Helping Domestic Violence Victims
Series: CS Colloquium
Abstract: Security often fails in practice due to a lack of understanding of the nuances in real-world systems. For example, users choose weak passwords to deal with the several usability issues with passwords, which in turn degrades the security of passwords. I will talk about how we can build better security mechanisms by combining methodical empiricism with analytical frameworks. First, in the context of passwords, I will show how to improve the usability of passwords by allowing users to log in with typos in their passwords. I will detail in the talk how to do so without giving attackers any additional advantage to impersonate a user.
In the second part of my talk, I will talk about my recent research direction on how traditional authentication mechanisms fail to properly model digital attacks by domestic abusers, and therefore are ineffective for victims. As a result, abusers can spy on, stalk, or harass victims using seemingly innocuous apps and technologies. I will finish with some recent progress that I have made in helping victims of tech abuse, and provide some future research directions.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Rahul Chatterjee is a Ph.D. candidate at Cornell University, working on computer security. Prior to joining Cornell, Rahul received his masters from the University of Wisconsin-Madison and bachelors from the Indian Institute of Technology (IIT), Kharagpur. Rahul's research focuses on user authentication, in particular passwords and biometrics. Lately, he is also conducting research on how to help stop technology abuse in the context of domestic violence. His co-authored papers have been covered by several media outlets, including The New York Times, and the MIT Tech Review. His work on password typos was recognized with the distinguished student paper award at IEEE S&P (2016).
Host: Muhammad Naveed
Location: Ronald Tutor Hall of Engineering (RTH) - 115
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Fall 2018 Joint CSC@USC/CommNetS-MHI Seminar Series
Mon, Mar 04, 2019 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Muriel Médard, MIT
Talk Title: Guessing Random Additive Noise Decoding (Grand)
Abstract: We introduce a new algorithm for Maximum Likelihood (ML) decoding based on guessing noise. The algorithm is based on the principle that the receiver rank orders noise sequences from most likely to least likely. Subtracting noise from the received signal in that order, the first instance that results in an element of the code-book is the ML decoding. For common additive noise channels, we establish that the algorithm is capacity achieving for uniformly selected code-books, providing an intuitive alternate approach to the channel coding theorem. When the code-book rate is less than capacity, we identify exact asymptotic error exponents as the block-length becomes large. We illustrate the practical usefulness of our approach in terms of speeding up decoding for existing codes.
Joint work with Ken Duffy, Kishori Konwar, Jiange Li, Prakash Narayana Moorthy, Amit Solomon.
Biography: Muriel Médard is the Cecil H. Green Professor in the Electrical Engineering and Computer Science (EECS) Department at MIT and leads the Network Coding and Reliable Communications Group at the Research Laboratory for Electronics at MIT. She has co-founded three companies to commercialize network coding, CodeOn, Steinwurf and Chocolate Cloud. She has served as editor for many publications of the Institute of Electrical and Electronics Engineers (IEEE), of which she was elected Fellow, and she has served as Editor in Chief of the IEEE Journal on Selected Areas in Communications. She was President of the IEEE Information Theory Society in 2012, and served on its board of governors for eleven years. She has served as technical program committee co-chair of many of the major conferences in information theory, communications and networking. She received the 2009 IEEE Communication Society and Information Theory Society Joint Paper Award, the 2009 William R. Bennett Prize in the Field of Communications Networking, the 2002 IEEE Leon K. Kirchmayer Prize Paper Award, the 2018 ACM SIGCOMM Test of Time Paper Award and several conference paper awards. She was co-winner of the MIT 2004 Harold E. Edgerton Faculty Achievement Award, received the 2013 EECS Graduate Student Association Mentor Award and served as Housemaster for seven years. In 2007 she was named a Gilbreth Lecturer by the U.S. National Academy of Engineering. She received the 2016 IEEE Vehicular Technology James Evans Avant Garde Award, the 2017 Aaron Wyner Distinguished Service Award from the IEEE Information Theory Society and the 2017 IEEE Communications Society Edwin Howard Armstrong Achievement Award. She is a member of the National Academy of Inventors.
Host: Prof. Urbashi Mitra, ubli@usc.edu
More Info: http://csc.usc.edu/seminars/2019Spring/medard.html
More Information: 19.03.04 Muriel Medard 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/2019Spring/medard.html
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CS Colloquium: Tatsunori Hashimoto (Stanford University) - Beyond the average case: machine learning for atypical examples
Tue, Mar 05, 2019 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Tatsunori Hashimoto, Stanford University
Talk Title: Beyond the average case: machine learning for atypical examples
Series: CS Colloquium
Abstract: Although machine learning systems have improved dramatically over the last decade, it has been widely observed that even the best systems fail on atypical examples. For example, prediction models such as image classifiers have low accuracy on images from minority cultures, and generative models such as dialogue systems are often incapable of generating diverse, atypical responses. In this talk, I will discuss two domains where high performance on typical examples is insufficient.
The first is learning prediction models that perform well on minority groups, such as non-native English speakers using a speech recognition system. We demonstrate that models with low average loss can still assign high losses to minority groups, and this gap can amplify over time as minority users that suffer high losses stop using the model. We develop an approach using distributionally robust optimization that learns models that perform well over all groups and mitigate the feedback loop.
The second domain is learning natural language generation (NLG) systems, such as a dialogue system. It has been frequently observed that existing NLG systems which produce high-quality samples rely heavily on typical responses such as "I don't know" and fail to generate the full diversity of atypical but valid human responses.
We carefully quantify this problem through a new evaluation metric based on the optimal classification error between human- and model-generated text and propose a new, edit-based generative model of text whose outputs are both diverse and high-quality.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Tatsunori (Tatsu) Hashimoto is a 3rd year post-doc in the Statistics and Computer Science departments at Stanford, supervised by Professors Percy Liang and John Duchi. He holds a Ph.D from MIT where he studied random walks and computational biology under Professors Tommi Jaakkola and David Gifford, and a B.S. from Harvard in Statistics and Math. His work has been recognized in NeurIPS 2018 (Oral), ICML 2018 (Best paper runner-up), and NeurIPS 2014 Workshop on Networks (Best student paper).
Host: Yan Liu
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Civil and Environmental Engineering Seminar
Tue, Mar 05, 2019 @ 03:00 PM - 04:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Saahastaranshu R. Bhardwaj, PhD, Purdue University
Talk Title: Multi-Hazard Resilience: The Need of the Hour
Abstract: Climate change has resulted in novel hazard patterns, with increasing severity and probability of multi-hazard scenarios. The field of structural engineering requires innovative approaches to address the challenges posed by climate change (e.g., multi-hazards), and to explore new frontiers in science and engineering (e.g., space habitat systems). There is a push for developing resilient and sustainable structural systems to cater these needs of science and industry.
This seminar describes recent large-scale experimental and numerical investigations to evaluate the multi-hazard response of steel-plate composite and reinforced concrete walls. The investigations involved subjecting the specimens to combined loading scenarios (e.g., seismic and thermal loading, multi-axial loading, gravity and fire loading). A particularly challenging aspect of the experiments involving multi-hazard loads is the design and construction of test set-ups. The seminar presents the design of experiments and summarizes the observations. The analysis and design tools developed to consider interaction of multi-hazard loading are also discussed.
A resilient community comprises of resilient assets. The multi-hazard evaluation capabilities can be employed to develop innovative and resilient structures for habitation on earth and elsewhere! The talk includes a discussion of potential research areas that warrant innovative structural systems and / or multi-hazard evaluation.
Host: Sonny Astani Department of Civil and Environmental Engineering
Location: Ray R. Irani Hall (RRI) - 101
Audiences: Everyone Is Invited
Contact: Salina Palacios
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Epstein Institute Seminar - ISE 651
Tue, Mar 05, 2019 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Stan Uryasev, Professor, University of Florida
Talk Title: How to Supplement Risk Regulations to Avoid Industrial Catastrophes
Host: Dr. Suvrajeet Sen
More Information: March 5, 2019.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute Seminar Series
Wed, Mar 06, 2019 @ 03:00 AM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dorsa Sadigh, Computer Science and Electrical Engineering at Stanford University
Talk Title: Interactive Autonomy: A human-centered approach to learning and control
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: Today's society is rapidly advancing towards robotics systems that interact and collaborate with humans, e.g., semi-autonomous vehicles interacting with drivers and pedestrians, medical robots used in collaboration with doctors, or service robots interacting with their users in smart homes. Formalizing interaction is a crucial component in seamless collaboration and coordination between humans and today's robotics systems. In this talk, I will first discuss our recent results on efficient and active learning of predictive models of humans' preferences by eliciting comparisons from humans. I will then formalize interactive autonomy, and our approach in design of learning and control algorithms that influence humans in interactive settings. I will further analyze the global implications of human-robot interaction and its societal impacts in the setting of autonomous driving.
Biography: Dorsa Sadigh is an assistant professor in Computer Science and Electrical Engineering at Stanford University. Her research interests lie in the intersection of robotics, learning and control theory, and algorithmic human-robot interaction. Specifically, she works on developing efficient algorithms for autonomous systems that safely and reliably interact with people. Dorsa has received her doctoral degree in Electrical Engineering and Computer Sciences (EECS) at UC Berkeley in 2017, and has received her bachelor's degree in EECS at UC Berkeley in 2012. She is awarded the Amazon Faculty Research Award, the NSF and NDSEG graduate research fellowships as well as the Leon O. Chua departmental award departmental award.
Host: Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
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CS Colloquium: Behnam Neyshabur (New York University) - Why Do Neural Networks Learn?
Wed, Mar 06, 2019 @ 09:00 AM - 10:00 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Behnam Neyshabur, New York University
Talk Title: Why Do Neural Networks Learn?
Series: CS Colloquium
Abstract: Neural networks used in practice have millions of parameters and yet they generalize well even when they are trained on small datasets. While there exists networks with zero training error and a large test error, the optimization algorithms used in practice magically find the networks that generalizes well to test data. How can we characterize such networks? What are the properties of networks that generalize well? How do these properties ensure generalization?
In this talk, we will develop techniques to understand generalization in neural networks. Towards the end, I will show how this understanding can help us design architectures and optimization algorithms with better generalization performance.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Behnam Neyshabur is a postdoctoral researcher in Yann LeCun's group at New York University. Before that, he was a member of Theoretical Machine Learning program lead by Sanjeev Arora at the Institute for Advanced Study (IAS) in Princeton. In summer 2017, he received a PhD in computer science at TTI-Chicago where Nati Srebro was his advisor. He is interested in machine learning and optimization and his primary research is on optimization and generalization in deep learning.
Host: Haipeng Luo
Location: Ronald Tutor Hall of Engineering (RTH) - 109
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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CS Colloquium:Sida Wang (Princeton University) - Learning Adaptive Language Interfaces Through Interaction
Wed, Mar 06, 2019 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Sida Wang, Princeton University
Talk Title: Learning Adaptive Language Interfaces Through Interaction
Series: CS Colloquium
Abstract: The interactivity and adaptivity of natural language have the potential to allow people to better communicate with increasingly AI-driven computer systems. However, current natural language interfaces are mostly static and fall short of their potential. In this talk, I will cover two systems that can quickly learn from interactions, adapt to users, and simultaneously give feedback so that users can adapt to the system. The first system learns from scratch from users in real time. The second starts with a programming language and then learns to naturalize the programming language by interacting with users. Finally, I will present how these ideas can be combined to build a natural language interface for data visualization and discuss my work on modeling interactive language learning more rigorously.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Sida Wang is a research instructor at Princeton University and Institute for Advanced Study working in the areas of natural language processing and machine learning. He holds a Ph.D. in computer science from Stanford University and a B.A.Sc. from the University of Toronto. He received an outstanding paper award at ACL 2016 and the NSERC Postgraduate Scholarship.
Host: Joseph Lim
Location: Ronald Tutor Hall of Engineering (RTH) - 115
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute Seminar Series
Wed, Mar 06, 2019 @ 11:30 AM - 12:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Vijay G. Subramanian, Electrical Engineering and Computer Science, University of Michigan
Talk Title: One If By Land and Two If By Sea: A Glimpse into the Value of Information in Strategic Interactions
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: This work studies sequential social learning (also known as Bayesian observational learning), and how private communication can enable agents to avoid herding to the wrong action/state. Starting from the seminal BHW (Bikhchandani, Hirshleifer, and Welch, 1992) model where asymptotic learning does not occur, we allow agents to ask private and finite questions to a bounded subset of their predecessors. While retaining the publicly observed history of the agents and their Bayes rationality from the BHW model, we further assume that both the ability to ask questions and the questions themselves are common knowledge. Then interpreting asking questions as partitioning information sets, we study whether asymptotic learning can be achieved with finite capacity questions. Restricting our attention to the network where every agent is only allowed to query her immediate predecessor, an explicit construction shows that a 1-bit question from each agent is enough to enable asymptotic learning.
This is joint work with Shih-Tang Su and Grant Schoenebeck at the University of Michigan. Details of the work can be found at https://arxiv.org/abs/1811.00226
Biography: I am an Associate Professor in the EECS Department at the University of Michigan. My main research interests are in stochastic modeling, communications, information theory, and applied mathematics. A large portion of my past work has been on probabilistic analysis of communication networks, especially analysis of scheduling and routing algorithms. In the past, I have also done some work with applications in immunology and coding of stochastic processes. My current research interests are on game-theoretic and economic modeling of socio-technological systems and networks, and the analysis of associated stochastic processes.
Host: Ashutosh Nayyar
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
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Astani Civil and Environmental Engineering Seminar
Wed, Mar 06, 2019 @ 11:30 AM - 12:30 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Lorenzo Valdevit, Ph.D., University of California, Irvine
Talk Title: Deformation and Damage Mechanisms in Ceramic Nano-Architected Metamaterials
Abstract: See attached
Host: Dr. Qiming Wang
More Information: Seminar Annoucement_Lorenzo Valdevit.docx
Location: Ray R. Irani Hall (RRI) - 101
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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The Role of Advanced Experimental and Numerical Simulations in the Management of Deteriorated Infrastructure
Wed, Mar 06, 2019 @ 03:00 PM - 04:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Hussam Mahmoud, PhD, Colorado State University
Talk Title: The Role of Advanced Experimental and Numerical Simulations in the Management of Deteriorated Infrastructure
Host: Civil and Environmental Engineering
Location: Ray R. Irani Hall (RRI) - 101
Audiences: Everyone Is Invited
Contact: Salina Palacios
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AME Seminar
Wed, Mar 06, 2019 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Krishna Garikipati, University of Michigan
Talk Title: Mechano-Chemical Phase Transformations: Computational Framework, Machine Learning Studies and Graph Theoretic Analysis
Abstract: Phase transformations in a wide range of materials-”for energy, electronics, structural and other applications-”are driven by mechanics in interaction with chemistry. We have developed a general theoretical and computational framework for large scale simulations of these mechano-chemical phenomena. I will begin by presenting our recent work in this sphere, while highlighting some of its more insightful results. In addition to being a platform for investigating mechanically driven phenomena in materials physics, this work is a foundation to explore the potential of recent advances in data-driven modeling. Of interest to us are machine learning advances that may enhance our approaches to solve computational materials physics problems. I will outline the first of several recent studies that we have launched in this spirit. Such combinations of classical high-performance scientific computing and modern data-driven modeling now allow us to access large numbers of states of physical systems. They also motivate the study of mathematical structures for representation, exploration and analysis of systems by using these collections of states. With this perspective, I will offer a view of graph theory that places it in nearly perfect correspondence with properties of stationary and dynamical systems. This has opened up new insights to our earlier, large-scale computational investigations of mechano-chemically phase transforming materials systems. This treatment has potential for eventual decision-making for physical systems that builds on high-fidelity computations.
Krishna Garikipati is a computational scientist whose work draws upon nonlinear physics, applied mathematics and numerical methods. A very recent interest of his is the development of methods for data-driven computational science. He has worked for quite a few years in mathematical biology, biophysics and materials physics. Some specific problems he has been thinking about recently are: (1) mathematical models of patterning and morphogenesis in developmental biology, (2) mathematical and physical modeling of tumor growth, and (3) mechano-chemically driven phenomena in materials, such as phase transformations and stress-influenced mass transport.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://ame.usc.edu/seminars/
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CAIS Seminar: Lindsay Young (University of Chicago) - Social Network Analysis and Artificial Intelligence: Methodological Partners in the Study of HIV Prevention and Risk Online
Wed, Mar 06, 2019 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Lindsay Young, University of Chicago
Talk Title: Social Network Analysis and Artificial Intelligence: Methodological Partners in the Study of HIV Prevention and Risk Online
Series: USC Center for Artificial Intelligence in Society (CAIS) Seminar Series
Abstract: As transmitters of information and progenitors of behavioral norms, social networks are critical mechanisms of HIV prevention and risk in impacted populations like men who have sex with men (MSM), people who inject drugs (PWID), and homeless youth. Today, widespread use of online social networking technologies (e.g., Facebook, Instagram, Twitter) yield unprecedented amounts of relational and communication data far richer than anything previously collected in offline (physical) network settings. However, parsing these complex data into tractable insights and solutions requires an innovative and flexible computational toolkit that extends beyond traditional approaches. In this talk, Dr. Young will discuss her ongoing efforts to unpack how HIV prevention and risk manifest in the Facebook networks of young MSM using a hybrid of computational methods that include social and semantic network analysis and machine learning approaches for textual analysis and predictive modeling. She will conclude with a discussion of the practical implications of this work and outstanding challenges that require further exploration.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Dr. Lindsay Young is a NIH Pathway to Independence Award Postdoctoral Fellow at the University of Chicago Department of Medicine and Chicago Center for HIV Elimination (CCHE). Trained as a social scientist and network methodologist, she now applies those perspectives to understand the social and communicative contexts of HIV risk and prevention among young sexual minorities and other vulnerable populations. She is particularly interested in how online social network data can be leveraged for behavioral research and interventions.
Host: Milind Tambe
Location: James H. Zumberge Hall Of Science (ZHS) - 252
Audiences: Everyone Is Invited
Contact: Computer Science Department
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CS Colloquium: Eunsol Choi (University of Washington) - Learning to Understand Entities In Text
Thu, Mar 07, 2019 @ 09:30 AM - 10:30 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Eunsol Choi, University of Washington
Talk Title: Learning to Understand Entities In Text
Series: CS Colloquium
Abstract: Real world entities such as people, organizations and countries play a critical role in text. Reading offers rich explicit and implicit information about these entities, such as the categories they belong to, relationships they have with other entities, and events they participate in. In this talk, we introduce approaches to infer implied information about entities, and to automatically query such information in an interactive setting. We expand the scope of information that can be learned from text for a range of tasks, including sentiment extraction, entity typing and question answering. To this end, we introduce new ideas for how to find effective training data, including crowdsourcing and large-scale naturally occurring weak supervision data. We also describe new computational models, that represent rich social and conversation contexts to tackle these tasks. Together, these advances significantly expand the scope of information that can be incorporated into the next generation of machine reading systems.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Eunsol Choi is a Ph.D candidate at the Paul G. Allen School of Computer Science at the University of Washington. Her research focuses on natural language processing, specifically applying machine learning to recover semantics from text. She completed a B.A. in Computer Science and Mathematics at Cornell University, and is a recipient of the Facebook fellowship.
Host: Xiang Ren
Location: Ronald Tutor Hall of Engineering (RTH) - 109
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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CS Colloquium: Chi Jin (UC Berkeley) Machine Learning: Why Do Simple Algorithms Work So Well?
Thu, Mar 07, 2019 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Chi Jin, UC Berkely
Talk Title: Machine Learning: Why Do Simple Algorithms Work So Well?
Series: CS Colloquium
Abstract: While state-of-the-art machine learning models are deep, large-scale, sequential and highly nonconvex, the backbone of modern learning algorithms are simple algorithms such as stochastic gradient descent, or Q-learning (in the case of reinforcement learning tasks). A basic question endures---why do simple algorithms work so well even in these challenging settings?
This talk focuses on two fundamental problems: (1) in nonconvex optimization, can gradient descent escape saddle points efficiently? (2) in reinforcement learning, is Q-learning sample efficient? We will provide the first line of provably positive answers to both questions. In particular, we will show that simple modifications to these classical algorithms guarantee significantly better properties, which explains the underlying mechanisms behind their favorable performance in practice.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Chi Jin is a Ph.D. candidate in Computer Science at UC Berkeley, advised by Michael I. Jordan. He received a B.S. in Physics from Peking University. His research interests lie in machine learning, statistics, and optimization, with his PhD work primarily focused on nonconvex optimization and reinforcement learning.
Host: Haipeng Luo
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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NL Seminar: Separating the Sheep from the Goats: On Recognizing the Literal and Figurative Usages of Idioms
Thu, Mar 07, 2019 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Rebecca Hwa, University of Pitt
Talk Title: Separating the Sheep from the Goats: On Recognizing the Literal and Figurative Usages of Idioms
Series: Natural Language Seminar
Abstract: Typically, we think of idioms as colorful expressions whose literal interpretations don't match their underlying meaning. However, many idiomatic expressions can be used either figuratively or literally, depending on their contexts. In this talk, we survey both supervised and unsupervised methods for training a classifier to automatically distinguish usages of idiomatic expressions. We will conclude with a discussion about some potential applications.
Biography: Rebecca Hwa is an Associate Professor in the Department of Computer Science at the University of Pittsburgh. Her recent research focuses on understanding persuasion from a computational linguistics perspective. Some of her recent projects include: modeling student behaviors in revising argumentative essays, identifying symbolisms in visual rhetorics, and understanding idiomatic expressions. Dr Hwa is a recipient of the NSF CAREER Award. Her work has also been supported by NIH and DARPA.
Host: Xusen Yin
More Info: https://nlg.isi.edu/nl-seminar/
Location: Information Science Institute (ISI) - Conf Room #689
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: https://nlg.isi.edu/nl-seminar/
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ECE Seminar: Information and Incentives in Learning and Decision Making on Networks
Thu, Mar 07, 2019 @ 11:15 AM - 12:15 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Parinaz Naghizadeh, Postdoctoral Research Associate/ Purdue University and Princeton University Edge Lab
Talk Title: Information and Incentives in Learning and Decision Making on Networks
Abstract: Networks play a central role in determining the outcomes of a variety of socio-technological and economic interactions. Examples include investing in security, sharing of congestible resources, and learning by teams of agents, in network environments. In this talk, I aim to analyze the role of information and incentives in distributed learning and decision making in such problems.
I will first discuss the role of information sharing in a multi-agent (reinforcement) learning problem. We study learning and decision making by agents who have heterogeneous information about their unknown, partially observable environment. We identify two benefits of information sharing between such agents: it facilitates coordination among them, and further enhances the learning rate of both better informed and less informed agents. We show however that these benefits will depend on the communication timing, in that delayed information sharing may be preferred in certain scenarios.
I will then present a framework for characterizing the effects of the network topology on strategic decision making over networks. Specifically, we establish a connection between the equilibrium outcomes of network games with non-linear (resp. linear) best-response functions, and variational inequality (resp. linear complementarity) problems. Through these connections, we outline conditions for existence, uniqueness, and stability of equilibria in these games, extending several existing results in the literature. We further discuss the effects of the network topology on the design of incentive mechanisms in such settings, with applications in improving cybersecurity.
Biography: Parinaz Naghizadeh is a postdoctoral research associate in the Department of Electrical and Computer Engineering at Purdue University and Princeton University Edge Lab. She received her Ph.D. in electrical engineering from the University of Michigan in 2016, M.Sc. degrees in electrical engineering and mathematics, both from the University of Michigan, in 2013 and 2014, respectively, and her B.Sc. in electrical engineering from Sharif University of Technology, Iran, in 2010. Her research interests are in network economics, learning theory, game theory, reinforcement learning, and data analytics. She was a recipient of the Barbour Scholarship in 2014, a finalist for the ProQuest Dissertation Award in 2016, and a Rising Stars in EECS in 2017.
Host: Professor Richard Leahy, leahy@sipi.usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute Seminar Series
Fri, Mar 08, 2019 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Ziv Bar-Joseph, Carnegie Mellon University
Talk Title: Distributed Information Processing in Biological and Computational Systems
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: Computer science and biology have enjoyed a long and fruitful relationship for decades. Computational methods are widely used to analyze and integrate large biological data sets, while several algorithms were inspired by the high-level design principles of biological systems. In this talk I will discuss similarities and differences between assumptions, requirements and goals of distributed biological and computational systems. To illustrate the mutual benefits I will present examples from two recent studies. The first models bacterial food search as an application of probabilistic belief propagation while the second looks at epigenetics as a process implementing a shared memory communication model.
Biography: Ziv Bar-Joseph is the FORE Systems Professor of Computational Biology and Machine Learning at the School of Computer Science at Carnegie Mellon University. His work focuses on the analysis, integration and modeling of high throughput biological data and on improving algorithms for distributed computational networks by relying on our increased understanding of how biological systems operate. Dr. Bar-Joseph received his Ph.D. from MIT in 2003. He is the director of the joint CMU-Pitt PhD program in Computational Biology and the PI of a number of large, multi-university centers including the HuBMAP Computational Tools Center. He was the recipient of the DIMACS-Celera Genomics Graduate Student Award in Computational Biology, the NSF CAREER award and Overton prize in computational biology.
Host: Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
Audiences: Everyone Is Invited
Contact: Talyia White
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W.V.T. RUSCH ENGINEERING HONORS COLLOQUIUM
Fri, Mar 08, 2019 @ 01:00 PM - 01:50 PM
USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Nathan Smith, Associate Curator, The Dinosaur Institute, Natural History Museum
Talk Title: The Assembly of Avian Anatomy -“from Early Dinosaurs to Diving Waterbirds
Host: EHP and Dr. Prata
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Amanda McCraven
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Mingu Kang Seminar, Friday, March 8th at 2PM in EEB 132
Fri, Mar 08, 2019 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Mingu Kang, IBM Thomas J. Watson Research Center
Talk Title: Energy-efficient machine learning in resource-constrained edge-computing platforms
Abstract: There is much interest in embedding data analytics into sensor-rich platforms such as wearables, biomedical devices, autonomous vehicles, robots, and Internet-of-Things (IoT) to provide these with decision-making capabilities. Such platforms need to implement machine learning algorithms under severe resource-constraints in embedded battery-powered platforms. However, traditional von Neumann architectures suffer from explicit separation between memory and computation (the "Memory Wall"), which imposes bottlenecks on energy efficiency and throughput for big data processing.
In this talk, I will present deep in-memory computing architecture (DIMA), where analog computation is deeply embedded into a standard memory array to overcome the memory wall. First, the data flow of machine learning algorithms is analyzed to show how it naturally leads to the DIMA. Next, the design of a multi-functional DIMA IC prototype will be presented to validate the concept of DIMA and demonstrate its versatility. An in-memory instruction set architecture with LLVM-based compiler is demonstrated to provide user-friendly programming interface, and optimal resource allocation for target application accuracy. DIMA lends itself to a communication-inspired system analysis that helps to understand the fundamental trade-off between its energy and accuracy in the low-SNR regime. Finally, I will present future research directions spanning device, architecture, and system to build large-scale system-on-chip by leveraging non-conventional computing including in-memory, in-sensor, and neuromorphic computing.
Biography: Mingu Kang is a research staff member of the IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA, where he designs machine learning accelerator architecture. He received the Ph.D. degree in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign, Champaign, IL, USA, in 2017, and the B.S. and M.S. degrees in Electrical and Electronic Engineering from Yonsei University, Seoul, South Korea, in 2007 and 2009, respectively. From 2009 to 2012, he was with the Memory Division, Samsung Electronics, Hwaseong, South Korea, where he was involved in the circuit and architecture design of phase change memory (PRAM). His current research interests include low-power integrated circuits, architecture, and system for machine learning and signal processing by leveraging emerging computing paradigms. He is a recipient of UIUC Coordinated Science Lab (CSL) best thesis award in 2018, MICRO TOP Pick Honorable Mention 2019, IEEE International Symposium on Circuits and Systems (ISCAS) "Neural System and Application" Best Paper Awards in 2016 and 2018, and Kwanjeong Scholarship from 2012 to 2017.
Host: ECE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Civil and Environmental Engineering
Fri, Mar 08, 2019 @ 03:00 PM - 04:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Xu Huang, University of Toronto
Talk Title: Large-Scale Computational/Experimental Distributed Simulation Framework
Host: Civil and Environmental Engineering
Location: Ray R. Irani Hall (RRI) - 101
Audiences: Everyone Is Invited
Contact: Salina Palacios
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Satellite Propulsion Systems
Sat, Mar 09, 2019 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Abstract: The Satellite Propulsion Systems program provides an understanding of the basic principles and figures of merit of Rocket Propulsion. Upon completion of the 4-day program, participants will be able to apply these principles to spacecraft propulsion system and components Analysis-&-Design, Testing, Ground Operations, Flight Operations, and End-of-life (EOL) De-orbit.
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/astronautical-engineering/satellite-propulsion-systems/
Audiences: Registered Attendees
Contact: Corporate & Professional Programs
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Six Sigma Green Belt for Process Improvement
Tue, Mar 12, 2019 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
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.
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-green-belt-process-improvement/
Audiences: Registered Attendees
Contact: Corporate & Professional Programs
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Advances in Seismic Performance Evaluation and Rehabilitation of Concentrically Braced Frames
Tue, Mar 12, 2019 @ 03:00 PM - 04:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Andrew Sen , PhD, University of Washington
Talk Title: Advances in Seismic Performance Evaluation and Rehabilitation of Concentrically Braced Frames
Host: Civil and Environmental Engineering
Location: Ray R. Irani Hall (RRI) - 101
Audiences: Everyone Is Invited
Contact: Salina Palacios
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**Spring Recess - No Epstein Seminar, ISE 651**
Tue, Mar 12, 2019 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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Six Sigma Green Belt for Process Improvement
Wed, Mar 13, 2019 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
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.
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-green-belt-process-improvement/
Audiences: Registered Attendees
Contact: Corporate & Professional Programs
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Six Sigma Green Belt for Process Improvement
Thu, Mar 14, 2019 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
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.
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-green-belt-process-improvement/
Audiences: Registered Attendees
Contact: Corporate & Professional Programs
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Satellite Propulsion Systems
Sat, Mar 16, 2019 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Abstract: The Satellite Propulsion Systems program provides an understanding of the basic principles and figures of merit of Rocket Propulsion. Upon completion of the 4-day program, participants will be able to apply these principles to spacecraft propulsion system and components Analysis-&-Design, Testing, Ground Operations, Flight Operations, and End-of-life (EOL) De-orbit.
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/astronautical-engineering/satellite-propulsion-systems/
Audiences: Registered Attendees
Contact: Corporate & Professional Programs
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CS Colloquium: Gang Wang (Virginia Tech) - Human Augmentation for Internet Security
Mon, Mar 18, 2019 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Gang Wang, Virginia Tech
Talk Title: Human Augmentation for Internet Security
Series: CS Colloquium
Abstract: Human factors are playing a critical role in the security of today's Internet systems. On one hand, human factors are constantly exploited by attackers to launch serious attacks, leading to massive data breaches and ransomware infections. On the other hand, human (expert) intelligence is instrumental in detecting and combating new threats (e.g., zero-days) that automated methods such as machine learning often fail to capture.
In this talk, I will describe our efforts to improve security through human augmentation. Human augmentation includes (1) reducing the security risks introduced by human factors, and (2) integrating human intelligence to build more robust security defenses. First, I will describe our progress to reduce the risk of human factors by detecting and mitigating flawed system designs that severely weaken user-level defenses. Using spear phishing as an example, I will illustrate how data analytics and active measurements can make a key difference in this process. Second, I will share our recent results on improving the trust and robustness of security systems by generating "human-interpretable" outputs. By building an "explanation system" for deep learning based security applications, we allow security analysts to diagnose classification errors and patch model weaknesses. Finally, I conclude by highlighting my future plans of using data-driven approaches to augmenting security defenses for both humans and algorithms.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Gang Wang is an Assistant Professor of Computer Science at Virginia Tech. He obtained his Ph.D. from UC Santa Barbara in 2016, and a B.E. from Tsinghua University in 2010. His research focuses on human (user) aspects of Internet security. His work takes a data-driven approach to addressing emerging security threats in massive communication systems (social networks, email services), crowdsourcing systems, mobile applications, and enterprise networks. He is a recipient of the NSF CAREER Award (2018), Google Faculty Research Award (2017), ACM CCS Outstanding Paper Award (2018), and SIGMETRICS Best Practical Paper Award (2013). His research has appeared in a diverse set of top-tier venues in Security, Measurement, Networking, and HCI. His projects have been covered by media outlets such as MIT Technology Review, The New York Times, Boston Globe, CNN, ACM TechNews, and New Scientist.
Host: Aleksandra Korolova
Location: Ronald Tutor Hall of Engineering (RTH) - 115
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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ECE Seminar: Communication Algorithms via Deep Learning
Mon, Mar 18, 2019 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Hyeji Kim, Researcher/Samsung AI Research Cambridge, UK
Talk Title: Communication Algorithms via Deep Learning
Abstract: The design of codes for communicating reliably over a statistically well-defined channel is an important endeavor involving deep mathematical research and wide-ranging practical applications. In this talk, we demonstrate that the discovery of decoding and coding algorithms can be automated via deep learning. We first show that creatively designed and trained Recurrent Neural Network (RNN) architectures can decode well known sequential codes such as convolutional and turbo codes with close to optimal performance on the additive white Gaussian noise (AWGN) channel, which itself is achieved by the Viterbi and BCJR algorithms. We also demonstrate that the neural network based decoders are much more robust and adaptive to deviations from the AWGN setting compared to existing decoders. Next, we present the first family of codes obtained via deep learning which significantly outperforms state-of-the-art codes. By integrating information theoretic insights into our design of recurrent-neural-network based encoders and decoders, we are able to construct the first set of practical codes for the Gaussian noise channel with feedback. Up until now, feedback has been known to theoretically improve the reliability of communication, but no practical codes have been able to do so.
Biography: Hyeji Kim is a researcher at Samsung AI Research Cambridge in the United Kingdom. Before she joined Samsung AI Research, she worked as a postdoctoral research associate at the University of Illinois at Urbana-Champaign. She received her Ph.D. and M.S. degrees in Electrical Engineering from Stanford University in 2016 and 2013, respectively, and her B.S. degree with honors in Electrical Engineering from KAIST in 2011. Her research interests include information theory, machine learning, and the interplay between the two areas. She is a recipient of the Stanford Graduate Fellowship and participant of the Rising Stars in EECS Workshop in 2015.
Host: Professor Salman Avestimehr, avestime@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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Fall 2018 Joint CSC@USC/CommNetS-MHI Seminar Series
Mon, Mar 18, 2019 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Margareta Stefanovic, University of Denver
Talk Title: Robust stabilization with guaranteed performance in heterogeneous multi-agent systems with nonlinear uncertain couplings
Abstract: Systems of physically interconnected multiple agents cooperating toward a common goal have received considerable attention lately, with applications in large-scale and cyber-physical systems. Distributed consensus ideas have been recognized as a more attractive approach compared to the centralized and decentralized ones. In this talk I will present recent results on stabilization, decoupling, and cooperative tracking in multi-agent systems subject to various types of challenges, such as mixed order linear dynamics, mixed matched/unmatched state-coupled nonlinear uncertainties in the agents dynamics. A unifying, easy-to-implement framework is developed using graph theory and optimal control formulation, to provide stability and guaranteed cost of the distributed communication topologies.
This is a joint work with the former PhD student and current postdoctoral DU research associate, Dr. Vahid Rezaei.
Biography: Margareta Stefanovic received a Ph.D. degree in Electrical Engineering (Control Systems) from the University of Southern California and is currently an Associate Professor of Electrical Engineering at the University of Denver. Her main research interests are in the areas of data-driven robust adaptive control, and distributed control of multi-agent systems. She serves as an Editor-at-Large for Journal of Intelligent and Robotic Systems and as an Associate Editor of ISA Transactions. Prof. Stefanovic is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE).
Host: Prof. Michael Safonov, msafonov@usc.edu
More Info: http://csc.usc.edu/seminars/2019Spring/stefanovic.html
More Information: 190318 Margareta Stefanovic 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/2019Spring/stefanovic.html
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CS Colloquium: ShiQing Ma (Purdue University) - Transparent Computing Systems Enabled by Program Analysis
Tue, Mar 19, 2019 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: ShiQing Ma, Purdue University
Talk Title: Transparent Computing Systems Enabled by Program Analysis
Series: CS Colloquium
Abstract: Modern computing systems are complex and opaque, which is the root cause of many security and software engineering problems. In enterprise level system operations, this leads to inaccurate and hard-to-understand attack forensics results. In deep learning systems, such opaqueness prevents us from understanding the misclassifications and improving the model accuracy. Hence, there is a pressing need for improving the transparency of these systems to help us solve the corresponding security and software engineering problems.
In this talk, I will focus on my research efforts of developing novel program analysis techniques to improve the transparency of such systems and their applications in attack forensics and deep learning systems. For attack forensics, I will first describe a compiler-based execution partitioning technique MPI which helps accomplish accurate, semantics-rich and multi-perspective attack forensics. For deep learning systems, I will introduce novel state differential analysis and input selection techniques to analyze deep learning model internals for addressing the misclassification problem. Finally, I will briefly present my ongoing and future work on intelligent systems (i.e., systems that combine traditional computing components and artificial intelligent components).
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Shiqing Ma is a Ph.D. candidate in the Department of Computer Science at Purdue University, co-advised by Professors Xiangyu Zhang and Dongyan Xu. His research interests lie in solving security and software engineering problems via program analysis techniques with a focus on improving the transparency of modern computing systems. He is the recipient of two Distinguished Paper Awards at ISOC NDSS 2016 and USENIX Security 2017
Host: Muhammad Naveed
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Myoung-Gyun Suh Seminar, Tuesday, March 19th at 2PM in EEB 132
Tue, Mar 19, 2019 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Myoung-Gyun Suh, California Institute of Technology
Talk Title: Optical microcombs: Towards ubiquitous precision measurements and beyond
Abstract: How do we make a precise clock? How do astronomers find Earth-like exoplanets? At the center of these questions lies a remarkable device, the Optical Frequency Comb. Optical frequency combs, or rulers of light, have revolutionized precision spectroscopy and metrology by enabling two distinct functions: first, the measurement of optical frequency with an unprecedented precision, and second, the counting of cycles of an optical field. The former has enabled the most accurate spectroscopy tools, new forms of LIDAR and astronomical calibration instruments used in the search for exoplanets, while the latter has enabled a new generation of optical clocks with accuracy orders-of-magnitude better than the current time standard[1].
In recent years, a miniature optical frequency comb (or microcomb) has been demonstrated using chip-based optical micro-resonators. Microcombs offer the prospect of shifting advanced metrology and spectroscopy tools from the realm of laboratory-scale systems to compact portable systems, thereby creating new research opportunities in mobile or space-borne instrumentation[2]. In this talk, I will introduce the principle of microcomb generation and recent developments in microcomb research including our work using high-Q silica micro-resonators[3-5]. Initial results in several application areas including spectroscopy[6], optical communications[7] and astronomy[8] will also be reviewed. Finally, after discussing challenges and opportunities in microcomb research, I will conclude by looking forward at opportunities enabled by microcomb technology, including precision spectroscopy, astronomy, and quantum information science.
Biography: Myoung-Gyun Suh is an experimental physicist in the Department of Applied Physics and Material Science at the California Institute of Technology (Caltech), where he has studied nonlinear optics using optical micro-resonators. His recent work focuses on developing novel chip-based optical sources (Brillouin lasers and micro-resonator soliton optical frequency combs) and exploring applications of these devices for optical sensors, precision spectroscopy, optical communications, and astronomy. He received his Ph.D. in Applied Physics from Caltech in 2017, M.S. in Physics from the National Taiwan University (NTU) in 2006, and B.S. in Physics from the Korea Advanced Institute of Science and Technology (KAIST) in 2004. He is a recipient of Taiwan scholarship and Kwanjeong scholarship. In his earlier research career, he was fascinated by interesting light-matter interaction phenomena in photonics crystal structures and he studied two-dimensional photonic crystal lasers for his B.S. and M.S. degrees. After completing his M.S., Dr. Suh worked at Samsung Advanced Institute of Technology (2006 - 2011) where he developed high efficiency Gallium Nitride light emitting diodes and III-V multi-junction solar cells.
Host: ECE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Epstein Institute Seminar - ISE 651
Tue, Mar 19, 2019 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Kaibo Liu, Assistant Professor, University of Wisconsin-Madison
Talk Title: Big Data Analytics for Real-time Complex System Monitoring and Prognostics
Host: Dr. Qiang Huang
More Information: March 19, 2019.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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Legion: Programming Heterogeneous, Distributed Parallel Machines
Tue, Mar 19, 2019 @ 03:30 PM - 05:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Alex Aiken , Stanford University
Talk Title: Legion: Programming Heterogeneous, Distributed Parallel Machines
Abstract: Programmers tend to think of parallel programming as a problem of dividing up computation, but often the most difficult part is the placement and movement of data. As machines become more complex and hierarchical, describing what to do with the data is increasingly a first-class programming concern. Legion is a programming model and runtime system for describing hierarchical organizations of both data and computation at an abstract level. A separate mapping interface allows programmers to control how data and computation are placed onto the actual memories and processors of a specific machine. This talk will present the design of Legion, the novel issues that arise in both the design and implementation, and experience with applications.
Biography: Alex Aiken is the Alcatel-Lucent Professor of Computer Science at Stanford. Alex received his Bachelors degree in Computer Science and Music from Bowling Green State University in 1983 and his Ph.D. from Cornell University in 1988. Alex was a Research Staff Member at the IBM Almaden Research Center (1988-1993) and a Professor in the EECS department at UC Berkeley (1993-2003) before joining the Stanford faculty in 2003. His research interest is in areas related to programming languages. He is an ACM Fellow, a recipient of Phi Beta Kappa's Teaching Award, and a former chair of the Stanford Computer Science Department (2014-18).
Host: Xuehai Qian, xuehai.qian@usc.edu
More Information: 19.03.19 Alex Aiken_CENG Seminar.pdf
Location: Ronald Tutor Hall of Engineering (RTH) - 211
Audiences: Everyone Is Invited
Contact: Brienne Moore
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CS Colloquium: Protiva Rahman (Ohio State University) - Amplifying Domain Expertise in Data Pipelines
Tue, Mar 19, 2019 @ 04:00 PM - 05:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Protiva Rahman, Ohio State University
Talk Title: Amplifying Domain Expertise in Data Pipelines
Series: Computer Science Colloquium
Abstract: Digitization of forms and electronic health records (EHR) has made data from diverse domains available for analysis. The specialized nature of the data require domain expert input at every step of the data analysis pipeline, including entry, cleaning, and analysis. Since domain experts (e.g. physicians) are highly skilled in their fields, their time is very valuable and expensive. Moreover, they often do not have any training in computer science or statistics, making it difficult for them to effectively interact with data. Thus, it is crucial that we make data interaction easy, efficient and effortless for experts. This involves amplifying or generalizing their inputs to multiple data points, reducing their time and effort.
In this talk, I will present Icarus, a system that leverages the database schema to amplify domain expert input during data cleaning. Icarus optimizes a weighted sum to guide the user to high-impact edits. Once a user fills in a cell, the system leverages the many-to-one relations in the database to suggest generalized update queries in the form of rules. These rules apply to a larger number of cells, amplifying the user's single edit.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Protiva Rahman is a fourth-year Ph.D. student in the Department of Computer Science and Engineering at the Ohio State University, advised by Professor Arnab Nandi. Her research interests include databases, human-computer interaction, visualization, and clinical informatics. Besides data cleaning, she has also worked on optimizing data entry interfaces for constrained interaction, guidelines for evaluating interactive systems and visualizations for domain expert consensus.
Host: Computer Science Department
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Computer Science Department
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ECE Seminar: Harnessing Nature to Make Wireless Positioning Practical and Accurate
Wed, Mar 20, 2019 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Manikanta Kotaru, Ph.D. Candidate, Stanford University
Talk Title: Harnessing Nature to Make Wireless Positioning Practical and Accurate
Abstract: Positioning has been the Holy Grail of wireless sensing research with a wide range of applications from tracking virtual reality devices to in-body implants. However, despite two decades of active research, a widely deployable system with high accuracy has always been elusive. Wireless signals reflected from objects in the environment interfere with and distort the signal from the intended target device, corrupting the position estimates. In order to fight this 'multipath' phenomenon, previous approaches built specialized wireless devices with huge antenna arrays or large bandwidths making them impractical for ubiquitous deployment. In this talk, I will introduce a new technique called 'Synthetic Aperture Radio' that harnesses, rather than fighting, the multipath that naturally occurs in the environment and exploits the device motion that naturally occurs in these applications. By applying this technique, I have demonstrated the first real-time and centimeter-level accurate positioning system using standard, off-the-shelf WiFi radios. Building on synthetic aperture radio technique, I have developed practical positioning systems for indoor navigation, tracking virtual reality accessories and resource constrained devices like endoscopic capsules. Looking forward, these techniques lay a foundation for utilizing ubiquitous wireless devices for developing important machine vision applications in various domains like medical sensing, physical security and autonomous vehicles.
Biography: Manikanta Kotaru is a Ph.D. candidate in Electrical Engineering at Stanford University. His research focuses on building widely-accessible computational sensing systems with applications in robotics, virtual reality, Internet of Things and medical sensing. His research bridges RF sensing and machine vision, and brings theory and systems together. His work has appeared in premier conferences in both communications and computer vision such as SIGCOMM and CVPR. He is a recipient of Stanford Graduate Fellowship.
Updated: 03/15/2019
Host: Professor Pierluigi Nuzzo, nuzzo@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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AME Seminar
Wed, Mar 20, 2019 @ 11:00 AM - 12:00 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Ananya Renuka Balakrishna, University of Minnesota
Talk Title: Microstructural Engineering Of Energy-Related Materials
Abstract: Future advances in aerospace engineering depend on developing materials with enhanced properties. For example, the next generation of electric aircrafts will need light-weight low-fatigue materials, high-performance sensing and actuation materials, and high-density energy storage materials. Material properties can be drastically enhanced by tuning the materials microstructural features. In my research, I develop and apply phase-field methods to investigate how microstructures form and evolve in materials, and how we can engineer these microstructures to enhance material properties. In this talk, I will present applications of phase-field modeling to two material systems: electro-mechanical -ferroelectrics- and chemo-mechanical -batteries- systems. First, I will show how microstructural engineering of ferroelectric materials generate actuation strains several times greater than piezoceramics in market. Second, I will show that not only the electrodes microstructures but also their crystallographic texture can be tailored to enhance battery materials mechanical strength. Overall, the phase-field models developed in my research provide a theoretical and computation framework to engineer next generation aerospace materials with enhanced properties and extended lifespans.
Ananya Balakrishna is a postdoctoral researcher at the University of Minnesota investigating microstructures in magnetic and light-interactive materials. She completed her PhD in Solid Mechanics and Materials Engineering at the University of Oxford, before pursuing postdoctoral research at MIT as a Lindemann Postdoctoral fellow. Broadly, her research focuses on developing mathematical models to investigate the links between material microstructures and properties in energy storage and functional materials. Her research on engineering ferroelectric microstructures has been recognized by the Falling Walls London Lab prize, and the British Federation for Women Graduates Award. She has also won other awards including the ASME Best student paper award, and the Felix scholarship for her graduate study.
Host: AME Department
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Tessa Yao
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute Seminar Series
Wed, Mar 20, 2019 @ 03:00 PM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Antonis Papachristodoulou, University of Oxford
Talk Title: Exploiting Sparsity in Semidefinite and Sum of Squares Programming
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: Semidefinite and sum of squares optimization have found a wide range of applications, including control theory, fluid dynamics, machine learning, and power systems. In theory they can be solved in polynomial time using interior-point methods. However, these methods are only practical for small- to medium- sized problem instances.
For large instances, it is essential to exploit or even impose sparsity and structure within the problem in order to solve the associated programs efficiently. In this talk I will present recent results on the analysis and design of networked systems, where chordal sparsity can be used to decompose the resulting SDPs, and solve an equivalent set of smaller semidefinite constraints. I will also discuss how sparsity and operator-splitting methods can be used to speed up computation of large SDPs and introduce our open-source solver CDCS. Lastly, I will extend the decomposition result on SDPs to SOS optimization with polynomial constraints, revealing a practical way to connect SOS optimization and DSOS/SDSOS optimization for sparse problem instances.
Biography: Antonis Papachristodoulou joined the University of Oxford in 2006, where he is currently Professor of Engineering Science and a Tutorial Fellow in Worcester College. Since 2015, he has been EPSRC Fellow and Director of the EPSRC & BBSRC Centre for Doctoral training in Synthetic Biology. He holds an MA/MEng in Electrical and Information Sciences from the University of Cambridge (2000) and a PhD in Control and Dynamical Systems from the California Institute of Technology, with a PhD Minor in Aeronautics (2005). In 2015 he was awarded the European Control Award for his contributions to robustness analysis and applications to networked control systems and systems biology and the O. Hugo Schuck Best Paper Award. He is an IEEE Fellow for contributions to the analysis and design of networked control systems. He serves regularly on Technical Programme Committees for conferences, and was associate editor for Automatica and IEEE Transactions on Automatic Control.
Host: Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
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CAIS Seminar: Robin Petering, Nick Barr, & AJ Srivastava - MyPath: Intervention for Reduction in Violence among at Risk Youth
Wed, Mar 20, 2019 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Robin Petering, Dr. Nick Barr, & Dr. AJ Srivastava,
Talk Title: MyPath: Intervention for Reduction in Violence among at Risk Youth
Series: USC Center for Artificial Intelligence in Society (CAIS) Seminar Series
Abstract: One in ten young people between ages 18-25 experience homelessness every year in the United States. The lives of youth experiencing homelessness is characterized by violence, more so than their housed counterparts. This is the result of several, often co-occurring, risk factors such as experience of childhood trauma, subsistence survival strategies including drug and alcohol use, and exposure to perpetrators during street tenure. Violence has many consequences from physical injury to heightened mental health distress. Reducing exposure and engagement to violence is critical for safe and successful exit from homelessness. However, to date, implementing a violence reduction intervention in this community has had little success.
MyPath is a peer-based social network intervention designed to reduce experiences of violence in a community of young persons experiencing homelessness. MyPath utilizes strategic machine learning selection methods to identify potential Mindfulness and Yoga Peer Ambassadors and invites them to participate in an intensive 3-hour mindfulness and yoga retreat that relates the two practices to the impact of violence. The retreat is followed by weekly 1-hour trainer-facilitated mindfulness and yoga classes that are open for attendance of non-peer ambassadors as well. MyPath is novel in that it uses an algorithm, called ViolMin, to identify potential peer ambassadors, which takes into account the uncertainty in links of surveyed network data and identifies "influential" individuals in a network, those who have a history of violent behavior, and yet are open to intervention.
The MyPath Pilot was implemented in partnership with Safe Place for Youth (SPY) during the summer of 2018. During this project, eight Mindfulness and Yoga Peer Ambassadors, selected by the ViolMin algorithm, participated in the program. Six weeks after the introduction of the MyPath programming, pilot results showed a statistically significant reduction in violence. The number of young people involved in physical fights dropped by 40%. There was also an increase of 85% in number of individuals who practice regular mindfulness and yoga. Moreover, the selected Mindfulness and Yoga Peer Ambassadors were highly engaged in the program. One MyPath ambassador reflected on the program, "People think threatening and violence is the answer. If everyone did mindfulness we would be living in a semi-better world. I didn't know anything about mindfulness, all I did know was violence, how to protect myself. When I got to SPY, I learned mindfulness and learned how to relax with yoga. I feel like a different person when I do it."
Biography: Dr. Robin Petering is interested in improving the lives of young persons who experience homelessness through community-based research, policy advocacy and program implementation. Her research agenda focuses on reducing violence through innovative intervention approaches. @robinpetering
Dr. Nicholas Barr is a postdoctoral fellow interested in improving mental and behavioral health outcomes in populations at high risk for adverse experiences. His research agenda focuses on investigating the protective effects of mindfulness and emotion regulation.
Dr. Ajitesh Srivastava is a Postdoctoral Research Associate at Ming Hsieh Institute of Electrical Engineering. His research interests include Data Mining, Social Network Analysis, Graph Algorithms, Optimizations, and Parallel Computing.
Host: Milind Tambe
Location: James H. Zumberge Hall Of Science (ZHS) - 252
Audiences: Everyone Is Invited
Contact: Computer Science Department
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CS Colloquium: Amy Zhang (MIT) - Systems to Improve Online Discussion
Thu, Mar 21, 2019 @ 09:30 AM - 10:30 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Amy Zhang, MIT
Talk Title: Systems to Improve Online Discussion
Series: CS Colloquium
Abstract: Discussions online are integral to everyday life, affecting how we learn, work, socialize, and participate in public society. Yet the systems that we use to conduct online discourse, whether they be email, chat, or forums, have changed little since their inception many decades ago. As more people participate and more venues for discourse migrate online, new problems have arisen, and old problems have intensified. People are still drowning in information and must now juggle dozens of disparate discussion silos in addition. Finally, an unfortunately significant proportion of this online interaction is unwanted or unpleasant, with clashing norms leading to people bickering or getting harassed into silence. My research in human-computer interaction is on reimagining outdated designs towards designing novel online discussion systems that fix what's broken about online discussion. To solve these problems, I develop tools that empower users and communities to have direct control over their experiences and information. These include: 1) summarization tools to make sense of large discussions, 2) annotation tools to situate conversations in the context of what is being discussed, as well as 3) moderation tools to give users more fine-grained control over content delivery.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Amy X. Zhang is a graduate student at MIT's Computer Science and Artificial Intelligence Laboratory, focusing on human-computer interaction and social computing, and a 2018-19 Fellow at the Harvard Berkman Klein Center. She has interned at Microsoft Research and Google Research, received awards at ACM CHI and CSCW, and featured in stories by ABC News, BBC, CBC, and more. She has an M.Phil. in CS at University of Cambridge on a Gates Fellowship and a B.S. in CS at Rutgers, where she captained the Division I Women's tennis team. Her research is supported by a Google PhD Fellowship and an NSF Graduate Research Fellowship.
Host: Nora Ayanian
Location: Ronald Tutor Hall of Engineering (RTH) - 109
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Ming Hsieh Institute Medical Imaging Seminar Series
Thu, Mar 21, 2019 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Xingfeng Shao, Electrical Computer and Engineering, University of Southern California
Talk Title: Mapping Water Exchange Rate Across the Blood-Brain Barrier
Abstract: The blood-brain barrier maintains the homeostasis within the brain and the dysfunction of blood-brain barrier has been linked to multiple central nervous system diseases and psychiatric disorders. The purpose of this work is to present a novel MR pulse sequence and regularized modeling algorithm to quantify the water exchange rate, kw, across the blood-brain barrier without contrast, and to evaluate its clinical utility in a cohort of elderly subjects at risk of cerebral small vessel disease. Elderly subjects were recruited and underwent two MRIs to evaluate the reproducibility of the proposed technique. Correlation analysis was performed between kw and vascular risk factors, Clinical Dementia Rating scale, neurocognitive assessments, and white matter hyperintensities. kw was significantly higher in subjects with diabetes and hypercholesterolemia. Significant correlations between kw and vascular risk factors, Clinical Dementia Rating scale, executive/memory function, and the Fazekas scale of white matter hyperintensities were also observed. These results suggest that kw may serve as a surrogate imaging marker of cerebral small vessel disease and associated cognitive impairment.
Biography: Xingfeng Shao is a Ph.D. candidate in Dr. Danny JJ Wang's lab in USC Mark and Mary Stevens Neuroimaging and Informatics Institute (INI). He obtained his Bachelor degree in Engineering Physics at Tsinghua University in Beijing, China, and joined USC BME department as a Ph.D. student in 2016. His research focus on MRI pulse sequence development. With background in physics and neurobiology, he has developed several MRI sequences for arterial spin labeling (ASL) and proposed a novel technique to measure water permeability across the blood-brain barrier in-vivo.
Host: Professor Krishna Nayak
Location: Michelson Center for Convergent Bioscience (MCB) - 101
Audiences: Everyone Is Invited
Contact: Talyia White
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ECE Seminar: Millimeter-Wave Computational Imaging
Thu, Mar 21, 2019 @ 10:30 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Andreas Pedross-Engel, Postdoctoral Research Associate/University of Washington, Seattle
Talk Title: Millimeter-Wave Computational Imaging
Abstract: This talk gives an overview on mmWave computational imaging. Millimeter-wave (mmWave) imaging has many applications such as remote sensing, autonomous robotics, non-destructive testing, and security screening. Some recent imaging systems will be presented, including compressed sensing and sparse reconstruction to minimize the amount of mmWave hardware, an enhanced resolution stripmap mode (ERSM) that leverages emerging metasurface antennas to improve image resolution by up to 42%, and an orthogonal coded active illumination (OCAI) approach to mitigate hardware imperfections and improve sensitivity by more than 40 dB. Finally, I will present a partitioned inverse reconstruction algorithm, optimized for GPUs, that yields a speedup of up to 300x.
Biography: Andreas Pedross-Engel is a postdoctoral Research Associate in the Department of Electrical and Computer Engineering at the University of Washington, Seattle, WA, USA. He is also a co-founder of the millimeter-wave imaging firm ThruWave Inc. He received the Dipl.-Ing. degree and the Ph.D. degree from Graz University of Technology, Graz, Austria, in 2009 and 2014, respectively. His research interests include microwave and millimeter-wave imaging systems, wireless communications, and nonlinear- and mixed- signal processing. In 2018 he received the ASciNA Young Scientist Award from the Austrian Federal Ministry of Education, Science and Research. He is also the recipient of the CoMotion Commercialization Fellows Award from the University of Washington in 2017. Since 2017 he is a Senior Member of the IEEE.
Host: Professor Urbashi Mitra, ubli@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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CS Colloquium: Srijan Kumar (Stanford University) - Data Science for Healthy Online Interactions
Thu, Mar 21, 2019 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Srijan Kumar, Stanford University
Talk Title: Data Science for Healthy Online Interactions
Series: CS Colloquium
Abstract: The web enables users to interact with one another and shape opinion at an unprecedented speed and scale. However, the prevalence of disinformation and malicious users makes the web unsafe and unreliable, for example, 40% of users have experienced online harassment and platforms have disabled user comments because of trolling. In this talk, I will present data science methods that help us to create a better and safer web ecosystem for everyone. In particular, I will present methods to extract knowledge from the social graph structure and augment with behavior signals to characterize, detect, and mitigate the damage of disinformation and malicious users.
First, I will describe a graph mining collective classification algorithm to identify fake reviews on e-commerce platforms. The method learns trustworthiness scores from the user-to-product review network to identify sophisticated fraudsters. The method is currently being used in production at Flipkart, India's largest e-commerce platform. Next, I will present the first web-scale characterization of multiple account abuse in online discussions and my method of statistical analysis of user interaction graphs to detect them. Finally, I will show how learning embeddings from the social network structure helps to predict online conflicts and to mitigate their damage. These methods power online tools that help administrators in Reddit and Wikipedia.
I will conclude the talk by describing my future research directions that will enable us to proactively predict how malicious behavior will evolve in the future, both on web platforms and face-to-face interactions
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Srijan Kumar (https://stanford.edu/~srijan/) is a postdoctoral scholar in Computer Science at Stanford University. His research investigates data science and machine learning to create healthy online and offline interactions, focusing on developing methods to curb deception, misbehavior, and disinformation. His methods have had a tangible real-world impact and are being used at major tech companies, including Flipkart, Reddit, and Wikipedia. His research has received the ACM SIGKDD Doctoral Dissertation Award runner-up 2018, Larry S. Davis Doctoral Dissertation Award 2018, and WWW Best Paper Award runner-up 2017. His research is interdisciplinary and has been included in the curriculum at several universities, including UIUC, University of Michigan, and Stanford University. His research has been included in documentary (Familiar Shapes) and covered in popular press, including CNN, The Wall Street Journal, Wired, and New York Magazine. He did his Ph.D. in Computer Science from University of Maryland, College Park, and B.Tech. from Indian Institute of Technology, Kharagpur.
Host: Xiang Ren
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Astani Civil and Environmental Engineering Seminar
Thu, Mar 21, 2019 @ 04:00 PM - 05:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Issam Najm, Ph.D., PE, Water Quality Treatment Solutions, Inc., Los Angeles
Talk Title: Cyanotoxins in Drinking Water
Abstract: See Attachment
Host: Dr. Amy Childress
More Information: Dr. Najm Issam_ Seminar Announcement.pdf
Location: Michelson Center for Convergent Bioscience (MCB) - 102
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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W.V.T. RUSCH ENGINEERING HONORS COLLOQUIUM
Fri, Mar 22, 2019 @ 01:00 PM - 01:50 PM
USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Speaker: Mr. Steven Gitlin, Vice President of Corporate Strategy, AeroVironment
Talk Title: Imagine the Impossible
Host: EHP and Dr. Prata
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Amanda McCraven
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Wei Kong Seminar, Friday, March 22nd at 2PM in EEB 248
Fri, Mar 22, 2019 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Wei Kong, MIT
Talk Title: 2D/3D hybrid materials towards a multifunctional integration platform
Abstract: Our society is entering the era of Internet of Things (IoT), which will be built upon a massive network of electronics. Though ever-increasing speed in modern electronics has been a salient metric of progress, other factors such as cost effectiveness, power consumption, biocompatibility, multifunctionality have become equally important. In general, mainstream electronic materials processing fails to fulfill this plurality of requirements.
Additive stacking of two-dimensional (2D) materials is a promising solution due to its freedom in functional design and reduction of material redundancy. This talk will introduce a new discovery in extracting a monolayer from multi-layer 2D material stacks. Although counterintuitive, this method enables perfect 2D material stacking by providing uniform, monolayer, wafer scale 2D material building blocks for scalable electronic device fabrication.
The speaker will further introduce the new concept of additive stacking of ultrathin three-dimensional (3D) materials, which has been a missing part to the concept of additive fabrication of electronic materials. The discovery of "remote epitaxy" enables the fabrication of free-standing ultrathin 3D materials as the building blocks for functional stacking. Leveraging the past 50 years of development in conventional 3D materials, 3D material stacking allows immense freedom in electronic design, enabling enhanced device performance and new device architectures.
These two discoveries further allow the integration of 2D and 3D materials as a new research area, which will allow the discovery of new physical phenomena, and lead to the advancements in wearables, human/machine interface, renewable energy, integrated photonics and quantum computation.
Biography: Wei Kong is a postdoc researcher at MIT, specializing in multifunctional integration of ultrathin film 2D and 3D materials, including graphene, hBN, TMDCs, and III-V, III-nitride and oxide compound semiconductors. His interests are in material innovation for human/machine interfaces, renewable energy, wearable electronics, integrated photonics and quantum computation. He obtained his B.S. in Physics from Sun Yat-Sen University, M.S. and PhD. in ECE from Duke University working with Prof. April Brown. He is currently a Shell Energy fellow at MIT, working with Prof. Jeehwan Kim in the Department of Mechanical Engineering, where he is also associated with Research Laboratory of Electronics (RLE). His works have been published in Nature, Science, Nature Materials, and Nature Electronics.
Host: ECE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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CS Colloquium: Anand Iyer (University of California, Berkeley) - Scalable Systems for Large-Scale Dynamic Connected Data Processing
Mon, Mar 25, 2019 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Anand Iyer, University of California, Berkeley
Talk Title: Scalable Systems for Large-Scale Dynamic Connected Data Processing
Series: CS Colloquium
Abstract: As the proliferation of sensors rapidly make the Internet-of-Things (IoT) a reality, the devices and sensors in this ecosystem-”such as smartphones, video cameras, home automation systems and autonomous vehicles-”constantly map out the real-world producing unprecedented amounts of connected data that captures complex and diverse relations. Unfortunately, existing big data processing and machine learning frameworks are ill-suited for analyzing such dynamic connected data, and face several challenges when employed for this purpose.
In this talk, I will present my research that focuses on building scalable systems for dynamic connected data processing. I will discuss simple abstractions that make it easy to operate on such data, efficient data structures for state management, and computation models that reduce redundant work. I will also describe how bridging theory and practice with algorithms and techniques that leverage approximation and streaming theory can significantly speed up computations. The systems I have built achieve more than an order of magnitude improvement over the state-of-the-art and are currently under evaluation in the industry for real-world deployments.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Anand Iyer is a PhD candidate at the University of California, Berkeley advised by Prof. Ion Stoica. His research interest is in systems with a current focus on enabling efficient analysis and machine learning on large-scale dynamic, connected data. He is a recipient of the Best Paper Award at SIGMOD GRADES-NDA 2018 for his work on approximate graph analytics. Before coming to Berkeley, he was a member of the Mobility, Networking and Systems group at Microsoft Research India. He completed his M.S at the University of Texas at Austin.
Host: Barath Raghavan
Location: Ronald Tutor Hall of Engineering (RTH) - 115
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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ECE Seminar: Specification-Driven Design for Modular and Safe Robotics
Mon, Mar 25, 2019 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Petter Nilsson, Post-Doctoral Researcher, California Institute of Technology
Talk Title: Specification-Driven Design for Modular and Safe Robotics
Abstract: Robotic systems of tomorrow will be increasingly interconnected and operate among us, which implies a two-fold engineering challenge of great complexity and no tolerance for mistakes. This talk will explore specification-driven design methods that enforce or utilize formally written specifications for principled design, modularity, and decision-making.
The first part will be centered on safety-critical control via invariance: I will show how invariance specifications in the form of assume-guarantee contracts can be leveraged to decompose problems and thus enable modular design, and how certificates for invariance can be used to formally relate low-level dynamics to a high-level abstract roadmap for planning. The second part of the talk will cover specification-guided methods for multi-robot systems, and how problem structure can be leveraged to overcome scalability challenges. The talk will be concluded with a few words about current research topics and directions for the future.
Biography: Petter Nilsson received his B.S. in Engineering Physics in 2011, and his M.S. in Optimization and Systems Theory in 2013, both from KTH Royal Institute of Technology in Stockholm, Sweden, and his Ph.D. in Electrical Engineering in 2017 from the University of Michigan. In addition to his technical degrees, he holds a B.S. in Business and Economics from the Stockholm School of Economics.
He is currently a postdoctoral scholar at the California Institute of Technology where he conducts research on specification-driven control and autonomy for safety-critical cyber-physical systems, with applications in autonomous driving, space exploration, and multi-agent coordination.
Host: Professor Justin Haldar, jhaldar@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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Fall 2018 Joint CSC@USC/CommNetS-MHI Seminar Series
Mon, Mar 25, 2019 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Michael Demetriou, Worcester Polytechnic Institute
Talk Title: Dynamic-data driven real-time estimation of plumes using adaptive sampling
Abstract: The goals in disaster management, characterized by hazardous plumes in indoor or outdoor environments, are the quickest detection of the disaster presence, its prompt reconstruction and the adaptive evacuation policy. In this talk, a very particular type of disaster is considered, namely the one resulting in hazardous plumes that are harmful to humans, and possibly to equipment. Such plumes are modeled by advection-diffusion partial differential equations with static or mobile sources that release harmful substances to the environment. The goal is to reconstruct the plume in real time, capturing all features of the plume. A model-based state estimator of the plume concentration is proposed and which combines estimation techniques with computational fluid dynamics and smart computing to arrive at real-time implementable plume concentration estimators. Some of the challenges in implementing a real-time state reconstruction scheme are presented. Solutions to these challenges are presented and include the use of mobile sensors to improve spatial resolution, spatial grid switching and refinement/coarsening for computational load reduction, and domain decomposition methods for code parallelization.
Biography: Michael Demetriou is a Professor of Aerospace Engineering at the Worcester Polytechnic Institute. He received his PhD degree from USC in Electrical Engineering-Systems in 1993. He served as an Associate Editor for the IEEE Transactions on Automatic Control, the ASME Journal of Dynamic Systems, Measurement, and Control, and the SIAM Journal on Control and Optimization. In 2003 he established the IEEE-CSS Technical Committee on Distributed Parameter Systems and he served as his first chair (2003-2012). He currently serves as the Secretary of the SIAM Control and Systems Theory activity group, as a member of the SIAM/SIAG Advisory Committee, and as a member of the SIAG/CST Conference Steering Committee. He is the IEEE/CSS-SIAM/SIAG Liaison and is serving as the SIAM Director in the the American Automatic Control Council (AACC) Board. His current research interests include optimization and control of mobile sensor and actuator networks in spatially distributed systems with applications to intrusion detection and containment.
Host: Petros A Ioannou, ioannou@usc.edu
More Info: http://csc.usc.edu/seminars/2019Spring/demetriou.html
More Information: 190325_Michael Demetriou.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Brienne Moore
Event Link: http://csc.usc.edu/seminars/2019Spring/demetriou.html
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CS Colloquium: TBA
Tue, Mar 26, 2019 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: TBA, TBA
Talk Title: TBA
Series: CS Colloquium
Host: Ramesh Govindan
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Epstein Institute Seminar - ISE 651
Tue, Mar 26, 2019 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Maryam Fazel, Associate Professor, University of Washington
Talk Title: The Many Faces of Regularization: from Signal Recovery to Online Algorithms
Host: Dr. Meisam Razaviyayn
More Information: March 26, 2019_room change.pdf
Location: Ronald Tutor Hall of Engineering (RTH) - 115
Audiences: Everyone Is Invited
Contact: Grace Owh
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Special Q&A Session with Albert Dorman
Tue, Mar 26, 2019 @ 08:00 PM - 09:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Albert Dorman, Founder and Past Chairman of the Board, AECOM Technology Corporation
Talk Title: Special Q&A Session with Albert Dorman
Host: Professor Henry Koffman
Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 116
Audiences: Everyone Is Invited
Contact: Salina Palacios
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ECE Seminar: Exploiting Terrain Responses for Effective Locomotion in Complex Environments
Wed, Mar 27, 2019 @ 10:30 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Feifei Qian, Postdoctoral Researcher, GRASP Lab, University of Pennsylvania
Talk Title: Exploiting Terrain Responses for Effective Locomotion in Complex Environments
Abstract: Today, robots are expected to take on increasingly important roles in human society. However, state-of-the-art robots still struggle to move on natural terrain, due to the lack of understanding of the interactions between robots and non-flat, non-rigid surfaces. My research aims to generate simplified models and representations of locomotor-terrain interactions, and improve robot mobility in complex environments.
In this talk, I will demonstrate how I integrate granular physics, bio-inspired robotics, and locomotion biomechanics to create interaction models that can guide design and control of bio-inspired robots to produce effective movement on challenging terrains. First, I will briefly review my previous work of animal and robot locomotion on granular terrain such as sand, debris, and gravel, and discuss how locomotors can manipulate granular responses and achieve effective locomotion on sand through adjustments in morphological parameters or contact strategy. Then I will present my recent work on creating simplified representations of robot interaction with perturbation-rich environments such as cluttered rubble or fallen tree trunks, and discuss how a multi-legged robot can adjust its gait patterns to exploit obstacle disturbances and generate different dynamics from the same physical environment. I will conclude with a vision of how these models and representations can lead to innovative strategies for obstacle-aided locomotion, better understanding of animal gait transition behaviors, and embodied sensing of environment properties.
Biography: Feifei Qian is currently a postdoctoral researcher in the GRASP lab at University of Pennsylvania. She received her PhD degree in Electrical Engineering from Georgia Tech in 2015. She is interested in understanding interactions between legged robots and complex terrains, and creating solutions for robots to exploit obstacles and disturbances to improve mobility. Her work was awarded the best student paper at Robotics: Science and Systems, and has been covered by media press including BBC, R&D Magazine, Phys.org, and PennCurrent.
Host: Professor Paul Bogdan, pbogdan@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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Mathematical Foundations of Learning from Signals and Data (Math-FLDS)
Wed, Mar 27, 2019 @ 03:00 PM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Alex Cloninger, University of California, San Diego
Talk Title: Crafting Laplacian Eigenfunctions to the Data Science Task
Series: MHI
Abstract: We will discuss two topics related to the importance of selecting particular eigenfunctions of the graph Laplacian. First, we discuss the geometry of Laplacian eigenfunctions on compact manifolds and combinatorial graphs. We will use a notion of similarity between eigenfunctions that allows to reconstruct a dual geometry, which recovers classical duals in particular cases. We will focus on the applications of discovering such a dual geometry, namely in constructing anisotropic graph wavelet packets and anisotropic graph cuts. A second topic will be the relevance of selecting import eigenfunctions for two sample testing, namely kernel Maximum Mean Discrepancy. This creates a more powerful test than the classical MMD while still maintaining sensitivity to common departures. We examine this two-sample testing in several medical examples.
Biography: Alex Cloninger is an Assistant Professor of Mathematics at UCSD. He received his PhD in Applied Mathematics and Scientific Computation from the University of Maryland in 2014 and was then an NSF Postdoc and Gibbs Assistant Professor of Mathematics at Yale University until 2017, when he joined UCSD. Alex researches problems around the analysis of high dimensional data. He focuses on approaches that model the data as being locally lower dimensional, including data concentrated near manifolds or subspaces. These types of problems arise in a number of scientific disciplines, including imaging, medicine, and artificial intelligence, and the techniques developed relate to a number of machine learning and statistical algorithms, including deep learning, network analysis, and measuring distances between probability distributions
Host: Mahdi Soltanolkotabi and Paul Bogdan
More Information: Cloninger, Alex Seminar.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Gloria Halfacre
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AME Seminar
Wed, Mar 27, 2019 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Hangbo Zhao, Northwestern University
Talk Title: Advanced Manufacturing of Unconventional 3D Micro- and Meso-Structures: From Strain-Engineered Growth to Mechanically Guided Assembly
Abstract: The growing availability of methods for three-dimensional (3D) manufacturing methods has implications across diverse areas ranging from energy systems to microelectronics, yet few techniques offer the necessary capabilities in geometric complexity, materials compatibility and design versatility. In this talk, I will discuss two novel manufacturing approaches to creating 3D functional material systems that are not feasible by conventional manufacturing methods: 1) strain-engineered growth of complex 3D carbon nanotube microarchitectures, and 2) mechanically guided 3D assembly of a broad range of functional materials and electronics. I will show how strain-engineered growth of carbon nanotubes, in combination with conformal coatings, enables direct formation of hierarchically structured surfaces with tailorable mechanical and interfacial properties for controlling liquid wetting and adhesion. Next, I will describe novel manufacturing technologies that exploit structural buckling and local twisting to create morphable 3D mesoscale structures in diverse advanced materials, and show how these can be used to make tunable optical metamaterials. I will also outline a microphysiological platform fabricated by mechanically guide assembly for tissue engineering and biomedical research. I will conclude by discussing new opportunities in designing and manufacturing multifunctional, adaptive material systems.
Hangbo Zhao is currently a postdoctoral researcher in the Center for Bio-Integrated Electronics in Prof. John Rogers group at Northwestern University, where he works on multifunctional 3D materials systems and bio-integrated electronics for applications in tissue engineering and healthcare. He received his Ph.D. degree in the Department of Mechanical Engineering at MIT in 2017, supervised by Prof. A. John Hart. His Ph.D. thesis focused on developing engineered, hierarchical surfaces for controlling liquid wetting and adhesion. He received his masters degree also in mechanical engineering at MIT in 2014, supervised by Prof. Carl V. Thompson. He received his bachelors degree in precision instruments at Tsinghua University in China in 2011.
Wednesday, March 27, 2019
3:30 PM
Seaver Science Library, Room 150 (SSL 150)
Refreshments will be served at 3:15 pm.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://ame.usc.edu/seminars/
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CS Colloquium: Abe Davis (Stanford University) - Augmenting Imagination: Capturing, Modeling, and Exploring the World Through Video
Thu, Mar 28, 2019 @ 09:30 AM - 10:30 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Abe Davis, Stanford University
Talk Title: Augmenting Imagination: Capturing, Modeling, and Exploring the World Through Video
Series: CS Colloquium
Abstract: Cameras offer a rich and ubiquitous source of data about the world around us, providing many opportunities to explore new computational approaches to real-world problems. In this talk, I will show how insights from art, science, and engineering can help us connect progress in visual computing with typically non-visual problems in other domains, allowing us to leverage the convenience and power of video to solve new problems. The first section of the talk will focus on visual vibration analysis: I will show how insights from physics can help us extract sound from silent video, reason about structural and material properties that are perceptually invisible to humans, and even build interactive physical simulations of visible objects. The second section of the talk will give an overview of how similar methodologies can be applied to artistic domains, using insights from music, dance, and cinematography to design computational tools that offer creative control over large amounts of media.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Abe Davis is a postdoctoral researcher at Stanford University working at the intersections of computer graphics, vision, HCI, and civil engineering. He earned his Ph.D. in Electrical Engineering and Computer Science from MIT in 2016 and is the recipient of the MIT Sprowls Award for Outstanding Dissertation in Computer Science and the ACM SIGGRAPH Outstanding Doctoral Dissertation Honorable Mention Award. Abe was awarded NSF and Mathworks graduate fellowships, named one of Forbes Magazine's "30 under 30", Business Insider's "50 Scientists Who are Changing the World" and "8 Innovative Scientists in Tech and Engineering." As a postdoc, he won the "Most Practical SHM Solution for Civil Infrastructures" Award at IWSHM 2017, and has been the recipient of two Magic Grants from the Brown Institute for Media Innovation.
Host: Jernej Barbic
Location: Ronald Tutor Hall of Engineering (RTH) - 109
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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ECE Seminar: Secure Computer Hardware in the Age of Pervasive Security Attacks
Thu, Mar 28, 2019 @ 10:30 AM - 11:45 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Mengjia Yan, PhD Candidate, University of Illinois, Urbana-Champaign
Talk Title: Secure Computer Hardware in the Age of Pervasive Security Attacks
Abstract: Recent attacks such as Spectre and Meltdown have shown how vulnerable modern computer hardware is. The root cause of the problem is that computer architects have traditionally focused on performance and energy efficiency. Security has never been a first-class requirement. Moving forward, however, this has to radically change: we need to rethink computer architecture from the ground-up for security.
As an example of this vision, in this talk, I will focus on speculative execution in out-of-order processors --- a core computer architecture technology that is the target of the recent attacks. I will describe InvisiSpec, the first robust hardware defense mechanism against speculative (a.k.a transient) execution attacks. The idea is to make loads invisible in the cache hierarchy, and only reveal their presence at the point when they are safe. Once an instruction is deemed safe, our hardware is able to cheaply modify the cache coherence state in a consistent manner. Further, to reduce the cost of InvisiSpec and increase its protection coverage, I propose Speculative Taint Tracking (STT). This is a novel form of information flow tracking that is specifically designed for speculative execution. It reduces cost by allowing tainted instructions to become safe early, and by effectively leveraging the predictor hardware that is ubiquitous in modern processors. Further improvements of InvisiSpec-STT can be attained with new compiler techniques. Finally, I will conclude my talk by describing ongoing and future directions towards designing secure processors.
Biography: Mengjia Yan is a Ph.D. student at the University of Illinois at Urbana-Champaign (UIUC), working with Professor Josep Torrellas. Her research interest lies in the areas of computer architecture and hardware security, with a focus on defenses against transient execution attacks and cache-based side channel attacks. Her work has appeared in some of the top venues in computer architecture and security, and has sparked a large research collaboration initiative between UIUC and Intel. Mengjia received the UIUC College of Engineering Mavis Future Faculty Fellow, the Computer Science W.J. Poppelbaum Memorial Award, a MICRO TopPicks in Computer Architecture Honorable Mention, and was invited to participate in two Rising Stars workshops.
Host: Professor Murali Annavaram, annavara@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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CS Colloquium: TBA
Thu, Mar 28, 2019 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: TBA, TBA
Talk Title: TBA
Series: CS Colloquium
Abstract: TBA
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: TBA
Host: Ramesh Govindan
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Architecture and Runtime for Scalable Quantum Computers
Fri, Mar 29, 2019 @ 10:30 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Moinuddin Qureshi , Georgia Institute of Technology
Talk Title: Architecture and Runtime for Scalable Quantum Computers
Abstract: Quantum computing promise exponential speedups for a class of important problems. However, this potential can be realized only by large-scale quantum systems that operate on a large number of qubits. Unfortunately, to build a scalable quantum computer several challenges must be overcome, including the design of conventional computing and memory systems that can effectively interface with the quantum substrate while obeying the thermal and power constraints dictated by the quantum devices. In this, talk, I will discuss some of our recent work in addressing the design challenges for the control computer for scalable quantum computers.
First, I will discuss our QuEST architecture from MICRO-50 that deals with taming the instruction bandwidth of quantum computers via hardware-managed Error Correction. Qubits are fickle and require continuous error correction. This can require an instruction bandwidth that must scale linearly with the number of qubits and can limit the scalability if error correction is managed in software. QuEST delegates the task of error correction to the hardware and uses programmable microcode to reduce the instruction bandwidth requirements. Second, I will discuss the feasibility of using DRAM-based memory system for Quantum Computers. Quantum computers will require significant memory that can operate at cryogenic temperatures. We characterized commodity DRAM at cryogenic environments and examined the minimum operating temperatures and nature of faults. Finally, I will discuss our upcoming work at ASPLOS 2019 that exploits variation in device error rate to improve the overall reliability of near-term quantum computers.
Biography: Moinuddin Qureshi is a Professor of Electrical and Computer Engineering at the Georgia Institute of Technology. His research interests include computer architecture, memory systems, hardware security, and quantum computing. Previously, he was a research staff member (2007-2011) at IBM T.J. Watson Research Center, where he developed the caching algorithms for Power-7 processors. He is a member of the Hall of Fame for ISCA, MICRO, and HPCA. His research has been recognized with the best paper award at MICRO 2018, best paper award at HiPC, and two selections (and three honorable mentions) at IEEE MICRO Top Picks. His ISCA 2009 paper on Phase Change Memory was awarded the 2019 Persistent Impact Prize in recognition of exceptional impact on the fields of study related to non-volatile memories. He was the Program Chair of MICRO 2015 and Selection Committee Co-Chair of Top Picks 2017. He received his Ph.D. (2007) and M.S. (2003) from the University of Texas at Austin
Host: Xuehai Qian, xuehai.qian@usc.edu
More Information: 190329_Moinuddin Qureshi.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Brienne Moore
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Astronautical Engineering (ASTE) - Seminar
Fri, Mar 29, 2019 @ 11:00 AM - 12:00 PM
Astronautical Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. Jonathan Black, Virginia Tech
Talk Title: Autonomy and Machine Learning in Space and Space Domain Awareness
Abstract: As resident space object populations grow, and satellite propulsion capabilities improve, it is becoming increasingly challenging for space-reliant nations to maintain space situational awareness using current human-in-the-loop methods. This presentation describes several real-time adaptive approaches to autonomous sensor network management for tracking multiple maneuvering and non-maneuvering satellites with a diversely populated Space Object Surveillance and Identification network. The methods integrate suboptimal Partially Observed Markov Decision Processes (POMDPs) with covariance inflation or multiple model adaptive estimation techniques to task sensors and maintain viable orbit estimates for all targets. Like in real-world situations, the population of target satellites vastly outnumbers the available set of sensors. Robust and adaptable tasking algorithms are needed in this scenario to determine how and when sensors should be tasked. The strategies successfully track hundreds of non-maneuvering and maneuvering spacecraft using only dozens of ground and space-based sensors. The results show that multiple model adaptive estimation coupled with a multi-metric, suboptimal POMDP can effectively and efficiently task a diverse network of sensors to track multiple maneuvering spacecraft, while simultaneously monitoring a large number of non-maneuvering objects. Overall, this work demonstrates the potential for autonomous and adaptable sensor network command and control for real-world space situational awareness.
Biography: Professor, Department of Aerospace and Ocean Engineering; Director, Aerospace and Ocean Systems Laboratory; Virginia Tech
Host: Astronautical Engineering - Mike Gruntman
More Information: 2019_03_29_ASTE-Seminar_Prof-Black_flier.pdf
Location: Vivian Hall of Engineering (VHE) - 217
Audiences: Everyone Is Invited
Contact: Mike Gruntman
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W.V.T. RUSCH ENGINEERING HONORS COLLOQUIUM
Fri, Mar 29, 2019 @ 01:00 PM - 01:50 PM
USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Speaker: Mr. Chris Tremmel and Mr. Vik Saraf, Co-General Managers, Jam City LA Studio
Talk Title: The Business of Mobile Gaming
Host: EHP and Dr. Prata
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Amanda McCraven
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J. Joshua Yang Seminar- Friday, March 29th at 2PM in EEB 132
Fri, Mar 29, 2019 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: J. Joshua Yang, University of Massachusetts
Talk Title: Unconventional Computing With Memristive Devices
Abstract: Memristive devices have become a promising candidate for energy-efficient and high-throughput unconventional computing, which is a key enabler for artificial intelligent systems in the big data and IoT era. The computing can be implemented on a Resistive Neural Network with memristive synapses and neurons or a Capacitive Neural Network with memcapacitive synapses and neurons. In this talk, I will first briefly introduce the promises and challenges of memristive devices and the key ideas behind bio-inspired computing. I will then discuss a few examples selected from our recent experimental demonstrations of unconventional computing using memristive networks with different levels of bio-inspiration: first, deep learning accelerators with supervised online learning; second, neuromorphic computing for pattern classification with unsupervised learning; last, other computing applications, such as reinforcement learning for decision making, artificial nociceptors for robotics, provable key destruction and true random number generators for cybersecurity.
Biography: Dr. J. Joshua Yang is a professor of the Department of Electrical and Computer Engineering at the University of Massachusetts, Amherst. Before joining UMass in 2015, he spent eight years at HP Labs and led the Memristive Materials and Devices team since 2012. His current research interests are Nanoelectronics and Nanoionics for computing and artificial intelligent systems, where he authored and co-authored over 140 technical papers and holds 110 granted and 55 pending US Patents. His MRAM patents were licensed by Intel, RRAM patents were technology-transferred to SK-hynix for memory development and recent patents at UMass led to a spin-off company on AI accelerators. He was named as a Spotlight Scholar of UMass Amherst in 2017. He obtained his PhD from the University of Wisconsin - Madison in the Material Science Program in 2007.
Host: ECE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Astronautical Engineering (ASTE) - Seminar
Fri, Mar 29, 2019 @ 02:00 PM - 03:00 PM
Astronautical Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. Jonathan Black, Virginia Tech
Talk Title: Autonomy and Machine Learning in Space and Space Domain Awareness
Abstract: As resident space object populations grow, and satellite propulsion capabilities improve, it is becoming increasingly challenging for space-reliant nations to maintain space situational awareness using current human-in-the-loop methods. This presentation describes several real-time adaptive approaches to autonomous sensor network management for tracking multiple maneuvering and non-maneuvering satellites with a diversely populated Space Object Surveillance and Identification network. The methods integrate suboptimal Partially Observed Markov Decision Processes (POMDPs) with covariance inflation or multiple model adaptive estimation techniques to task sensors and maintain viable orbit estimates for all targets. Like in real-world situations, the population of target satellites vastly outnumbers the available set of sensors. Robust and adaptable tasking algorithms are needed in this scenario to determine how and when sensors should be tasked. The strategies successfully track hundreds of non-maneuvering and maneuvering spacecraft using only dozens of ground and space-based sensors. The results show that multiple model adaptive estimation coupled with a multi-metric, suboptimal POMDP can effectively and efficiently task a diverse network of sensors to track multiple maneuvering spacecraft, while simultaneously monitoring a large number of non-maneuvering objects. Overall, this work demonstrates the potential for autonomous and adaptable sensor network command and control for real-world space situational awareness.
Biography: Professor, Department of Aerospace and Ocean Engineering; Director, Aerospace and Ocean Systems Laboratory; Virginia Tech
Host: Astronautical Engineering - Mike Gruntman
More Information: 2019_03_29_ASTE-Seminar_Prof-Black_flier.pdf
Location: Vivian Hall of Engineering (VHE) - 217
Audiences: Everyone Is Invited
Contact: Mike Gruntman
