SUNMONTUEWEDTHUFRISAT
Conferences, Lectures, & Seminars
Events for March
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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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
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
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor.
