SUNMONTUEWEDTHUFRISAT
Conferences, Lectures, & Seminars
Events for April
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ECE-S Seminar - Dr Ruohan Gao
Mon, Apr 03, 2023 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr Ruohan Gao, Postdoctoral Research Fellow | Department of Computer Science, Stanford University
Talk Title: Multisensory Machine Intelligence
Abstract: The future of Artificial Intelligence demands a paradigm shift towards multisensory perception-”to systems that can digest ongoing multisensory observations, that can discover structure in unlabeled raw sensory data, and that can intelligently fuse useful information from different sensory modalities for decision making. While we humans perceive the world by looking, listening, touching, smelling, and tasting, traditional form of machine intelligence mostly focuses on a single sensory modality, particularly vision. My research aims to teach machines to see, hear, and feel like humans to perceive, understand, and interact with the multisensory world. In this talk, I will present my research of multisensory machine intelligence that studies two important aspects of the multisensory world: 1) multisensory objects, and 2) multisensory space. In both aspects, I will talk about how I design systems to reliably capture multisensory data, how I effectively model them with new differentiable simulation algorithms and deep learning models, and how I explore creative cross-modal/multi-modal applications with sight, sound, and touch. In the end, I will conclude with my future plans.
Biography: Ruohan Gao is a Postdoctoral Research Fellow working with Prof. Fei-Fei Li, Prof. Jiajun Wu, and Prof. Silvio Savarese in the Vision and Learning Lab at Stanford University. He obtained his Ph.D. advised by Prof. Kristen Grauman at The University of Texas at Austin and B.Eng. at The Chinese University of Hong Kong. Ruohan mainly works in the fields of computer vision and machine learning with particular interests in multisensory learning with sight, sound, and touch. His research has been recognized by the Michael H. Granof Award which is designated for UT Austin's Top 1 Doctoral Dissertation, the Google PhD Fellowship, the Adobe Research Fellowship, a Best Paper Award Runner Up at British Machine Vision Conference (BMVC) 2021, and a Best Paper Award Finalist at Conference on Computer Vision and Pattern Recognition (CVPR) 2019.
Host: Dr Antonio Ortega, aortega@usc.edu
Webcast: https://usc.zoom.us/j/93551506449?pwd=SzF2UTRRL1ZSQjF4N3VMdDlsOEJwUT09More Information: ECE Seminar Announcement 04.03.2023 Ruohan Gao.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 248
WebCast Link: https://usc.zoom.us/j/93551506449?pwd=SzF2UTRRL1ZSQjF4N3VMdDlsOEJwUT09
Audiences: Everyone Is Invited
Contact: Miki Arlen
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-Controls Faculty Candidate Seminar - Dr Steve Alpern
Tue, Apr 04, 2023 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr Steve Alpern, Professor, University of Warwick
Talk Title: The Faulty GPS Problem: Optimal Search for Home Node on a Network, with Unreliable Directions
Abstract: Searcher wants to find the Home node on a given Network, but his directions are unreliable. At every branch node of a network Q, a Satnav (GPS) points to the arc leading to the destination, or home node, H - but only with a high known probability p. The pointer is fixed in time, so does not change when a node is revisited. Always trusting the Satnav's suggestion may lead to an infinite cycle. If one wishes to reach H in least expected time, with what probability q=q(Q,p) should one trust the pointer (if not, one chooses randomly among the other arcs)? We call this the Faulty Satnav (GPS) Problem. We also consider versions where the trust probability q can depend on the degree of the current node and a `treasure hunt' where two searchers try to reach H first. The agent searching for H need not be a car, that is just a familiar example -- it could equally be a UAV receiving unreliable GPS information.
This problem has its origin not in driver frustration but in the work of Fonio et al (2017) on ant navigation, where the pointers correspond to pheromone markers pointing to the nest.
Biography: Steve did his AB in Mathematics at Princeton, supervised by Oskar Morgenstern, and his PhD in Ergodic Theory at Courant Institute -“ NYU, under Peter Lax. He moved from ergodic theory to game theory and search theory mid career. After many years at the London School of Economics, he moved to the University of Warwick, where he is Professor of Operational Research.
Host: Dr Petros Ioannou, ioannou@usc.edu | Dr George Papavissilopoulos, yorgos@netmode.ece.ntua.gr
Webcast: https://usc.zoom.us/j/96085498483?pwd=aXJ4U244VHhQOCtIUURDM29mb216UT09More Information: ECE-Controls_Seminar_Announcement.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
WebCast Link: https://usc.zoom.us/j/96085498483?pwd=aXJ4U244VHhQOCtIUURDM29mb216UT09
Audiences: Everyone Is Invited
Contact: John Diaz
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. -
Photonics Seminar - Antonio Rigol, Tuesday, April 4th at 3pm in EEB 248
Tue, Apr 04, 2023 @ 03:00 PM - 04:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Marcos Antonio Rigol, Physics, Penn State
Talk Title: Typical eigenstate entanglement entropy as a diagnostic of quantum chaos and integrability
Series: Photonics Seminar Series
Abstract: The typical entanglement entropy of subsystems of random pure states is known to be (nearly) maximal, while the typical entanglement entropy of random Gaussian pure states has been recently shown to exhibit a qualitatively different behavior, with a coefficient of the volume law that depends on the fraction of the system that is traced out. We review evidence that the typical entanglement entropy of eigenstates of quantum-chaotic Hamiltonians mirrors the behavior in random pure states, while that of integrable Hamiltonians mirrors the behavior in random Gaussian pure states. Based on these results, we conjecture that the typical entanglement entropy of Hamiltonian eigenstates can be used as a diagnostic of quantum chaos and integrability. We discuss subtleties that emerge as a consequence of conservation laws, such as particle number conservation, as well as of lattice translational invariance.
Biography: Dr. Rigol is a Professor of Physics at Penn State. Before joining Penn State, he was an Associate Professor of Physics at Georgetown University. Dr. Rigol completed his undergraduate (Summa Cum Laude) and M.Sc. studies at the Institute of Nuclear Sciences and Technology in Havana. He received his Ph.D.
in Physics (Summa Cum Laude) from the University of Stuttgart, and did postdocs at the University of California Davis, the University of Southern California, and the University of California Santa Cruz.
Dr. Rigol research interest is in many-body quantum systems in and out of equilibrium, with a focus on the effect of strong correlations. His research is at the interface between condensed matter physics, ultracold atoms, and statistical mechanics. He is a Fellow of the American Physical Society and of the American Association for the Advancement of Science.
Host: Mercedeh Khajavikhan, Michelle Povinelli, Constantine Sideris; Hossein Hashemi; Wade Hsu; Mengjie Yu; Wei Wu; Tony Levi; Alan E. Willner; Andrea Martin Armani
More Information: Marcos Antonio Rigol Flyer.pdf
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-S Seminar - Dr Yi Ding
Thu, Apr 06, 2023 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr Yi Ding, Postdoctoral Associate & NSF Computing Innovation Fellow | CSAIL, MIT
Talk Title: A Holistic View on Machine Learning for Systems
Abstract: Improving computer system performance and resource efficiency are long-standing goals. Recent approaches that use machine learning methods to achieve these goals rely on a predictor that predicts the latency, throughput, or energy consumption of a sub-computation to, for example, aid hardware resource management or scheduling. In this talk, I will present a holistic view on machine learning for systems. I will demonstrate that maximizing machine learning prediction accuracy does not always optimize system behavior. Instead, my research vision focuses on a holistic view on machine learning for systems. The key insight in achieving this vision is understanding the cost structure of systems problems and then making proper tradeoffs between different steps within the process. Based on this vision, I will introduce a couple of machine learning for systems solutions to meet different system goals such as energy and performance. I will conclude the talk with my future directions.
Biography: Yi Ding is an NSF Computing Innovation Fellow and Postdoctoral Associate at MIT CSAIL. Her research interests focus on co-designing machine learning and systems approaches that enhance computer system performance and resource efficiency. She is a recipient of 2020 CRA/CCC/NSF Computing Innovation Fellowship, a Rising Stars in EECS Workshop participant, and a recipient of Meta Research Award. Before MIT, she received her PhD in computer science from the University of Chicago. Website: https://y-ding.github.io/.
Host: Dr Chris Torng, ctorng@usc.edu | Dr Massoud Pedram, pedram@usc.edu
Webcast: https://usc.zoom.us/j/91455259066?pwd=dHdrZnhtRUh2KzhDQnhUZHhaTmQ5QT09More Information: ECE Seminar Announcement 04.06.2023 - Yi Ding.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
WebCast Link: https://usc.zoom.us/j/91455259066?pwd=dHdrZnhtRUh2KzhDQnhUZHhaTmQ5QT09
Audiences: Everyone Is Invited
Contact: Miki Arlen
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-EP seminar - Dion Khodagholy
Fri, Apr 07, 2023 @ 09:30 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dion Khodagholy, Columbia University
Talk Title: Translational Neuroelectronics
Series: ECE-EP Seminar
Abstract: Our understanding of the brain's physiology and pathology is fueled by sophisticated bioelectronics that enable visualization and manipulation of neural circuits at multiple spatial and temporal resolutions. All components of these bioelectronic devices must be engineered with biocompatibility and clinical translation in mind. Organic electronics offer a unique approach to this device design, due to their mixed ionic/electronic conduction, mechanical flexibility, enhanced biocompatibility, and capability for drug delivery. We design, develop, and characterize conformable, stretchable organic electronic devices based on conducting polymer-based electrodes, particulate electronic composites, high-performance transistors, conformable integrated circuits, and ion-based data communication. We then use these devices in systems neuroscience experiments in animal models and humans to analyze neural network functions and facilitate new discoveries that could improve patient care.
These devices established new experimental paradigms that allowed discovery of novel brain oscillations and elucidated patterns of neural network maturation in the developing brain. Furthermore, these devices were used for intra-operative recording from patients undergoing epilepsy and deep brain stimulation surgeries, highlighting their translational potential. We have also leveraged them to form responsive electrical interventions that target biomarkers for memory consolidation and affect the progression of epilepsy.
To expand beyond neural interfaces to complete devices, we are developing fully-implantable, conformable implantable integrated circuits based on high-speed internal ion-gated organic electrochemical transistors that can perform the entire chain of signal acquisition, processing, and transmission without the need of hard Si-based devices. This multidisciplinary approach has permitted innovation of new organic electronic devices that could be leveraged establish a sustainable track of impactful bioelectronic inventions and address clinical applications such as brain-machine interfaces and therapeutic closed-loop devices.
Biography: Dion Khodagholy is an associate professor in the Department of Electrical Engineering, School of Engineering and Applied Science at Columbia University. He received his Master's degree from the University of Birmingham (UK) in Electronics and Telecommunication Engineering. This was followed by a second Master's degree in Microelectronics at the Ecole des Mines. He attained his Ph.D. degree in Microelectronics at the Department of Bioelectronics of the Ecole des Mines (France). He completed a postdoctoral fellowship as a Simon's Society fellow in systems neuroscience at New York University, Langone Medical Center. He is a recipient of the NSF CAREER award, junior fellow of Simons society, and SEAS Translational Award.
His research aims to use unique properties of materials for the purpose of designing and developing novel electronic devices that allow efficient interaction with biological substrates, and thereby enhancing our understanding of neural networks and brain function.
Host: ECE-Electrophysics
More Information: Dion Khodagholy Seminar Announcement.pdf
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-S Seminar - Dr Stephen Tu
Mon, Apr 10, 2023 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr Stephen Tu, Research Scientist at Google Brain (Robotics at Google)
Talk Title: The foundations of machine learning for feedback control
Abstract: Recent breakthroughs in machine learning offer unparalleled optimism for the future capabilities of artificial intelligence. However, despite impressive progress, modern machine learning methods still operate under the fundamental assumption that the data at test time is generated by the same distribution from which training examples are collected. In order to build robust intelligent systems-”self-driving vehicles, robotic assistants, smart grids-”which safely interact with and control the surrounding environment, one must reason about the feedback effects of models deployed in closed-loop.
In this talk, I will discuss my work on developing a principled understanding of learning-based feedback systems, grounded within the context of robotics. First, motivated by the fact that many real world systems naturally produce sequences of data with long-range dependencies, I will present recent progress on the fundamental problem of learning from temporally correlated data streams. I will show that in many situations, learning from correlated data can be as efficient as if the data were independent. I will then examine how incremental stability-”a core idea in classical control theory-”can be used to study feedback-induced distribution shift. In particular, I will characterize how an expert policy's stability properties affect the end-to- end sample complexity of imitation learning. I will conclude by showing how these insights lead to practical algorithms and data collection strategies for imitation learning.
Biography: Stephen Tu is a research scientist at Robotics at Google in New York City. His research interests are focused on a principled understanding of the effects of using machine learning models for feedback control, with specific emphasis on robotics applications. He received his Ph.D. from the University of California, Berkeley in EECS under the supervision of Ben Recht.
Host: Dr Mahdi Soltanolkotabi, soltanol@usc.edu
Webcast: https://usc.zoom.us/j/92463220973?pwd=UHJEVmZFV2V2L25zOUo1aDY0cTFNQT09More Information: ECE Seminar Announcement 04.10.2023 Stephen Tu.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 248
WebCast Link: https://usc.zoom.us/j/92463220973?pwd=UHJEVmZFV2V2L25zOUo1aDY0cTFNQT09
Audiences: Everyone Is Invited
Contact: Miki Arlen
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-S Seminar - Dr Sabrina Neuman
Tue, Apr 11, 2023 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr Sabrina Neuman, Postdoctoral NSF Computing Innovation Fellow | Harvard University
Talk Title: Designing Computing Systems for Robotics and Physically Embodied Deployments
Abstract: Emerging applications that interact heavily with the physical world (e.g., robotics, medical devices, the internet of things, augmented and virtual reality, and machine learning on edge devices) present critical challenges for modern computer architecture, including hard real-time constraints, strict power budgets, diverse deployment scenarios, and a critical need for safety, security, and reliability. Hardware acceleration can provide high-performance and energy-efficient computation, but design requirements are shaped by the physical characteristics of the target electrical, biological, or mechanical deployment; external operating conditions; application performance demands; and the constraints of the size, weight, area, and power allocated to onboard computing-- leading to a combinatorial explosion of the computing system design space. To address this challenge, I identify common computational patterns shaped by the physical characteristics of the deployment scenario (e.g., geometric constraints, timescales, physics, biometrics), and distill this real-world information into systematic design flows that span the software-hardware system stack, from applications down to circuits. An example of this approach is robomorphic computing: a systematic design methodology that transforms robot morphology into customized accelerator hardware morphology by leveraging physical robot features such as limb topology and joint type to determine parallelism and matrix sparsity patterns in streamlined linear algebra functional units in the accelerator. Using robomorphic computing, we designed an accelerator for a critical bottleneck in robot motion planning and implemented the design on an FPGA for a manipulator arm, demonstrating significant speedups over state-of-the-art CPU and GPU solutions. Taking a broader view, in order to design generalized computing systems for robotics and other physically embodied applications, the traditional computing system stack must be expanded to enable co-design with physical real-world information, and new methodologies are needed to implement designs with minimal user intervention. In this talk, I will discuss my recent work in designing computing systems for robotics, and outline a future of systematic co-design of computing systems with the real world.
Biography: Sabrina M. Neuman is a postdoctoral NSF Computing Innovation Fellow at Harvard University. Her research interests are in computer architecture design informed by explicit application-level and domain-specific insights. She is particularly focused on robotics applications because of their heavy computational demands and potential to improve the well-being of individuals in society. She received her S.B., M.Eng., and Ph.D. from MIT. She is a 2021 EECS Rising Star, and her work on robotics acceleration has received Honorable Mention in IEEE Micro Top Picks 2022 and IEEE Micro Top Picks 2023.
Host: Dr Feifei Qian, feifeiqi@usc.edu | Dr Pierluigi Nuzzo, nuzzo@usc.edu
Webcast: https://usc.zoom.us/j/98275605184?pwd=NVBvL2hKdEZCRFRSTm1Hb1RWTSs2QT09More Information: ECE Seminar Announcement 04.11.2023 - Sabrina Neuman.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
WebCast Link: https://usc.zoom.us/j/98275605184?pwd=NVBvL2hKdEZCRFRSTm1Hb1RWTSs2QT09
Audiences: Everyone Is Invited
Contact: Miki Arlen
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. -
Semiconductors & Microelectronics Technology Seminar - Qiushi Guo, Thursday, April 13th at 11am in EEB 248
Thu, Apr 13, 2023 @ 11:00 AM - 12:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Qiushi Guo, CUNY Advanced Science Research Center (ASRC)
Talk Title: Lithium niobate integrated nonlinear photonics: new devices and systems on an old material
Series: Semiconductors & Microelectronics Technology
Abstract: Despite being an old material in optical and microwave technologies in its bulk form, thin-film lithium niobate (TFLN) has recently emerged as one of the most promising integrated photonic platforms owing to its strong electro-optic (EO) coefficient, quadratic optical nonlinearity, and broadband optical transparency ranging from 250 nm to 5 um. In this talk, I will first overview the basic optical properties of LN, and how LN nanophotonics can grant us new regimes of nonlinear photonics. Then I will present some of our recent experimental results on the realization and utilization of dispersion-engineered and quasi-phase-matched ultrafast photonic devices in both classical and quantum domains. I will discuss the realization of 100 dB/cm optical parametric amplification, 1.5-3 um widely tunable optical parametric oscillator (OPO), ultra-wide bandwidth quantum squeezing, femtosecond and femtojoule on chip all-optical switching, and the integrated mode-locked lasers based on TFLN with watt-level peak power.
Biography: Qiushi Guo is an assistant professor at the Advanced Science Research Center, City University of New York. Prior to joining the ASRC and the CUNY Graduate Center, Qiushi was a postdoctoral research associate at the California Institute of Technology. He received his Ph.D. in Electrical Engineering from Yale University in Dec. 2019, advised by Prof. Fengnian Xia. He received his M.S. degree in Electrical Engineering from the University of Pennsylvania in 2014, and his B.S. degree in Electrical Engineering from Xi'an Jiaotong University in 2012. Qiushi is the finalist of the 2022 Rising Star of Light, and the winner of the 2021 Henry Prentiss Becton Graduate Prize for his exceptional research achievements at Yale University. His research interests include integrated nonlinear and quantum photonics, mid-infrared photonics, and 2-D materials optoelectronics. He has published more than 40 peer-reviewed research papers in leading scientific journals with citations more than 300 times. He is serving on the editorial board of the journal Micromachines.
Host: J Yang, H Wang, C Zhou, S Cronin, W Wu
More Information: Qiushi Guo_2023-4-13.pdf
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-S Seminar - Dr Gokul Subramanian Ravi
Mon, Apr 17, 2023 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr Gokul Subramanian Ravi, Postdoctoral Scholar | University of Chicago
Talk Title: A Hybrid Computing Ecosystem For Practical Quantum Advantage
Abstract: As quantum computing transforms from lab curiosity to technical reality, we must unlock its full potential to enable meaningful benefits on real-world applications with imperfect quantum technology. Achieving this vision requires computer architects to play a key role, leveraging classical computing principles to build and facilitate a hybrid computing ecosystem for practical quantum advantage.
First, I will introduce my four research thrusts toward building this hybrid ecosystem: Classical Application Transformation, Adaptive Noise Mitigation, Scalable Error Correction and Efficient Resource Management.
Second, from the Classical Application Transformation thrust, I will present "CAFQA: A classical simulation bootstrap for variational quantum algorithms", which enables accurate classical initialization for VQAs by searching efficiently through the classically simulable portion of the quantum space with Bayesian Optimization. CAFQA recovers as much as 99.99% of the accuracy lost in prior state-of-the-art classical initialization, with mean improvements of 56x.
Third, from the Scalable Error Correction thrust, I will present "Clique: Better than worst-case decoding for quantum error correction", which proposes the Clique QEC decoder for cryogenic quantum systems. Clique is a lightweight cryo-decoder for decoding and correcting common trivial errors, so that only the rare complex errors are handled outside the cryo-refrigerator. Clique eliminates 90-99+% of the cryo-refrigerator I/O decoding bandwidth, while supporting more than a million physical qubits.
Finally, I will conclude with an overview of other prior and ongoing work, along with my future research vision toward practical quantum advantage.
Biography: Gokul Subramanian Ravi is a 2020 NSF CI Fellows postdoctoral scholar at the University of Chicago, mentored by Prof. Fred Chong. His research targets quantum computing architecture and systems, primarily on themes at the intersection of quantum and classical computing. He received his PhD in computer architecture from UW-Madison in 2020 and was advised by Prof. Mikko Lipasti. He was awarded the 2020 Best ECE Dissertation Award from UW-Madison and named a 2019 Rising Star in Computer Architecture. His quantum and classical computing research have resulted in publications at top computer architecture, systems, and engineering venues, as well as two granted and three pending patents. His co-authored work was recognized as the Best Paper at HPCA 2022 and as a 2023 IEEE Micro Top Picks Honorable Mention.
Host: Dr Todd Brun, tbrun@usc.edu | Dr Christopher Torng, ctorng@usc.edu
Webcast: https://usc.zoom.us/j/97436018617?pwd=OFJVQ2Y0aCtnT0JXTE9LeWJlaGlvQT09More Information: ECE Seminar Announcement 2023.03.27 - Gokul Subramanian Ravi.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 248
WebCast Link: https://usc.zoom.us/j/97436018617?pwd=OFJVQ2Y0aCtnT0JXTE9LeWJlaGlvQT09
Audiences: Everyone Is Invited
Contact: Miki Arlen
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-S Seminar - Dr Paria Rashidinejad
Tue, Apr 18, 2023 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr Paria Rashidinejad, Postdoctoral Scholar | University of California, Berkeley
Talk Title: Reliable Data-Driven Decision-Making Systems
Abstract: Despite impressive success in domains such as vision and language, machine learning is still far from reliable integration into many challenging real-world scenarios, such as healthcare, where the coverage of existing data and the ability to collect new, diverse data are limited. This talk focuses on mathematically formulating and addressing some of the challenges in data-driven decision-making systems, studied in the reinforcement learning (RL) framework. I will discuss decision-making based on two sources of data: historical (offline) data and actively-collected data. In learning from offline data, I first mathematically formulate the challenge of partial data coverage. I show that this formulation combined with pessimistic offline RL unifies the major offline learning paradigms: imitation learning and conventional offline RL. I then present statistically-optimal and practical offline RL algorithms that simultaneously exploit expressive models, such as deep neural networks, and historical datasets with any coverage, to learn good decision-making policies. In learning from interactive data, I present general formulations and theoretically-guaranteed algorithms that exploit problem structure and expressive models to collect data for learning good policies, with efficacy demonstrated in a variety of navigation and locomotion tasks.
Biography: Paria Rashidinejad is a Postdoctoral Scholar at Berkeley AI Research Lab and Center for Human-Compatible AI. She received her Ph.D. in Electrical Engineering and Computer Sciences from the University of California, Berkeley in May 2022, under the supervision of Stuart Russell and Jiantao Jiao. Her research focuses on the mathematical foundations of machine learning and AI and designing capable and general-purpose AI and ML systems for reliable integration into the real world. She also works on machine learning applications in areas such as healthcare, robotics, and systems.
Host: Dr Somil Bansal, somilban@usc.edu | Dr Urbashi Mitra, ubli@usc.edu
Webcast: https://usc.zoom.us/j/95534730279?pwd=SWtyVk0zcWtkWUQ5WVltRlNMalpNZz09More Information: ECE Seminar Announcement 04.18.2023 - Paria Rashidinejad.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
WebCast Link: https://usc.zoom.us/j/95534730279?pwd=SWtyVk0zcWtkWUQ5WVltRlNMalpNZz09
Audiences: Everyone Is Invited
Contact: Miki Arlen
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. -
Photonics Seminar - Michael Shlesinger
Wed, Apr 19, 2023 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Michael Shlesinger, Office of Naval Research
Talk Title: Stretched Times and Divergent Time Scales Near the Glass Transition
Series: Photonics Seminar Series
Abstract: Near the glass transition temperature, Tg, many supercooled liquids experience stretched exponential relaxations rather than faster exponential decay. The relaxation has a time scale that diverges at a critical temperature, Tc, which is below Tg. I derive these laws from a model of anomalous defect diffusion and apply the theory to the pressure dependent conductivity of ion doped polymers near Tg. From a thermodynamic viewpoint comparisons are made of isochoric activation energy to isobaric activation enthalpy to determine the relative importance of volume and temperature to electrical conductivity. A key ingredient in the theory is the disappearance of free volume associated with defects when the temperature is lowered. The theory is able to explain the free volume measurements made by positron annihilation experiments.
Biography: Dr. Michael Shlesinger received a B.S. in Math and Physics from SUNY Stony Brook in 1970 and PhD in Physics from the University of Rochester in 1976. He then worked at the La Jolla Institute, Georgia Tech, and the University of Maryland before joining the Office of Naval Research in 1983. He became Head of ONR's Physics Division in 1986 and a member of the Senior Executive Service in 1987. He switched to a Chief Scientist role in 1995 and received the Presidential Rank Award in 2004 and ONR's Outstanding Lifetime Achievement Award in 2006. He has held the Kinnear Chair for Science at the USNA. One of his ONR responsibilities was the Division Director for Marine Corps programs. His ONR programs have focused on fields including Nonlinear Dynamics; Fractals; and Plasmonic Materials. He co-founded the Experimental Chaos Conference and received the APS Outstanding Referee Award. His work on random processes can be found in his 2021 mathematical autobiography "An Unbounded Experience in Random Walks with Applications".
Host: Mercedeh Khajavikhan, Michelle Povinelli, Constantine Sideris; Hossein Hashemi; Wade Hsu; Mengjie Yu; Wei Wu; Tony Levi; Alan E. Willner; Andrea Martin Armani
More Information: Michael Shlesinger Flyer.pdf
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. -
MHI ISSS Seminar - Prof. Yahya Tousi, Thursday, April 20th at 2pm in RTH 211
Thu, Apr 20, 2023 @ 02:00 PM - 02:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. Yahya Tousi, University of Minnesota, Twin Cities
Talk Title: Toward energy-efficient and scalable mm-wave systems
Series: Integrated Systems
Abstract: The end of device scaling is the dawning of a new era in integrated circuit design. Today, there is a growing demand for energy-efficient systems in multi-sensor electric vehicles, UAVs, and distributed wireless pico-cells. This is while, the intrinsic performance of analog building blocks no longer scales with technology nodes. In this talk I will argue that in the absence of device-level scaling, rethinking the frontend architecture by modernizing the traditional hierarchical design can open the door to substantial improvements in hardware efficiency and scalability. I will present two examples to support this claim.
In the first work we rethink digital processing in phase modulated radars by replacing it with a more efficient mixed analog processing scheme. The new system demonstrates more than an order of magnitude improvement in energy efficiency compared to traditional radar sensors. In the second work I introduce a nearest element phase monitoring architecture that overcomes the scalability challenges in traditional LO distribution schemes. Based on this new approach and for the first time, we implement a mm-wave phased array radiator with seamless multi-chip scalability. These two examples demonstrate how combining architectural and circuit-level innovations in this new era can lead to efficient and scalable mm-wave and THz systems.
Biography: Yahya Tousi received his Ph.D. degree in 2012 from the Department of Electrical and Computer Engineering at Cornell University, Ithaca, NY. In 2014 he joined the IBM T. J. Watson Research Center at Yorktown Heights, NY to develop the next generation of mm-wave phased array transceivers for wireless communication systems, and since 2017 he has been with the ECE Department at the University of Minnesota, Twin Cities. His current research interests are in high performance integrated circuits and novel architectures for mm-wave and terahertz systems with applications in communication, sensing, and healthcare. Dr. Tousi is the co-recipient of ISSCC Lewis Award for Outstanding Paper, and the Journal of Solid-State Best Paper Award both in 2017, the DARPA Young Faculty Award in 2020 and the DARPA Director's Fellowship Award in 2022.
Host: MHI - ISSS, Hashemi, Chen and Sideris
More Info: Zoom Link/Code: Meeting ID: 950 2226 0136, Passcode: 325523
More Information: FLYER_Tousi.pdf
Location: Ronald Tutor Hall of Engineering (RTH) - 211
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: Zoom Link/Code: Meeting ID: 950 2226 0136, Passcode: 325523
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. -
Pitfalls and Paradoxes in the History of Probability Theory
Fri, Apr 21, 2023 @ 10:30 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Michael Shlesinger, Office of Naval Research
Talk Title: Pitfalls and Paradoxes in the History of Probability Theory
Abstract: From the throwing of bones, dice, choosing long or short sticks, or debating the risk of the smallpox vaccine, fascinating and sometimes puzzling questions have arisen to advance the field of probability. We discuss interesting personalities and their famous questions and paradoxes including Galileo and Newton's dice game, de Mere's Grand Scandal, the Pascal-Fermat letters, the St. Petersburg Paradox, Bernoulli's Monster, and Bertrand's Paradox. We discuss the discovery of limit theorems from DeMoivre who first arrived at the Gaussian to Poisson who studied the same process, but with a twist arrived instead at the Poisson distribution. Levy considered a self-similar random process to arrive at random variables with infinite moments with now connections to fractals.
Biography: Dr. Michael Shlesinger received a B.S. in Math and Physics from SUNY Stony Brook in 1970 and PhD in Physics from the University of Rochester in 1976. He then worked at the La Jolla Institute, Georgia Tech, and the University of Maryland before joining the Office of Naval Research in 1983. He became Head of ONR's Physics Division in 1986 and a member of the Senior Executive Service in 1987. He switched to a Chief Scientist role in 1995 and received the Presidential Rank Award in 2004 and ONR's Outstanding Lifetime Achievement Award in 2006. He has held the Kinnear Chair for Science at the USNA. One of his ONR responsibilities was the Division Director for Marine Corps programs. His ONR programs have focused on fields including Nonlinear Dynamics; Fractals; and Plasmonic Materials. He co-founded the Experimental Chaos Conference and received the APS Outstanding Referee Award. His work on random processes can be found in his 2021 mathematical autobiography "An Unbounded Experience in Random Walks with Applications."
Host: Paul Bogdan
Location: Hedco Neurosciences Building (HNB) - 100
Audiences: Everyone Is Invited
Contact: Estela Lopez
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. -
MoBI Seminar: The Brain's Crescendo; How Music Training Impacts Child Development
Mon, Apr 24, 2023 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Assal Habibi, Associate Research Professor of Psychology, Brain and Creativity Institute, University of Southern California
Talk Title: The Brain's Crescendo; How Music Training Impacts Child Development
Abstract: In a multi-year longitudinal study, we have been investigating the effects of a group-based music training program on the development of children, beginning at age 6, using behavioral, neuroimaging, and electrophysiological measures. The target group of children have been participating in the Youth Orchestra of Los Angeles (YOLA) program. This music program is based on the Venezuelan system of musical training known as El-Sistema and offers free music instruction 6-“7 hours weekly to children from underprivileged and under-resourced areas of Los Angeles. The children in the music program have been compared with two groups of children, one involved in a community-based sports program, and another not enrolled in any systematic afterschool training. During this talk, I will share some of the behavioral and neuroimaging results from this study. Over the course of 5 years, we have observed that children in the music group had better performance than comparison groups in musically relevant auditory skills (pitch and rhythm discrimination) and showed an accelerated maturity of auditory processing as measured by cortical auditory evoked potentials. We also observed that children in the music group showed a different rate of cortical thickness maturation between the right and left posterior superior temporal gyrus and higher fractional anisotropy in the corpus callosum, specifically in the crossing pathways connecting superior frontal, sensory, and motor segments. For nonmusical skills, children with music training, compared with children without music training, showed stronger neural activation during a cognitive inhibition task in brain regions involved in response inhibition and decision-making (bilateral pre-SMA/SMA, ACC, IFG). Finally, we observed that parents of children involved in music training, after four years, rated their children higher on the emotional stability personality trait and lower on aggression and on hyperactivity compared to children not involved in music activities despite no differences in these measures before children's entry into the program. Considering a general reduction in art education specifically in the communities where there is limited access to art exposure in general, and specifically to music education, the findings from this study is providing compelling answers to the ongoing discussion about music's role in the education curriculum.
Biography: Assal Habibi is an Associate Research Professor of Psychology at the Brain and Creativity Institute at the University of Southern California. Her research takes a broad perspective on understanding the influence of arts and specifically music on health and development, focusing on how biological dispositions and learning experiences shape the brain and development of cognitive, emotional and social abilities during childhood and adolescence. She is an expert on the use of electrophysiologic and neuroimaging methods to investigate human brain function and has used longitudinal and cross-sectional designs to investigate how implementing music training programs within the school curricula impacts the learning and academic achievement of children from under-resourced communities. Her research program has been supported by federal agencies and private foundations including the NIH, NEA and the GRoW @ Annenberg Foundation and her findings have been published in peer reviewed journals including Cerebral Cortex, Music Perception, Neuroimage and PLoS ONE. Currently, she is the lead investigator of a multi-year study, in collaboration with the Los Angeles Philharmonic and their Youth Orchestra program (YOLA), investigating the effects of early childhood music education on the development of brain function and structure as well as learning skills, cognitive, emotional, and social abilities. Dr. Habibi is a classically trained pianist and has many years of musical teaching experience with children, a longstanding personal passion.
Host: Dr. Karim Jerbi, karim.jerbi.udem@gmail.com and Dr. Richard M. Leahy, leahy@sipi.usc.edu
Webcast: https://usc.zoom.us/j/99532928626?pwd=QjlwM2JGejZLdzNPdWEwc3RSNk0wdz09More Information: MoBI-Seminar-Habibi-042423.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 539
WebCast Link: https://usc.zoom.us/j/99532928626?pwd=QjlwM2JGejZLdzNPdWEwc3RSNk0wdz09
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.
