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Conferences, Lectures, & Seminars
Events for May
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CSC/CommNetS-MHI Seminar: Na Li
Thu, May 01, 2025 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Na Li, Winokur Family Professor of Electrical Engineering and Applied Mathematics, Harvard University | Visiting Researcher in Mitsubishi Electric Research Laboratories (MERL)
Talk Title: Representation-based Control and Reinforcement Learning for Dynamical Systems
Series: CSC/CommNetS-MHI Seminar Series
Abstract: The explosive growth of machine learning and data-driven methodologies have revolutionized numerous fields. Yet, the translation of these successes to the domain of dynamical physical systems remains a significant challenge. Closing the loop from data to actions in these systems faces many difficulties, stemming from the need for sample efficiency and computational feasibility, along with many other requirements such as verifiability, robustness, and safety. In this talk, we bridge this gap by introducing innovative representations to develop nonlinear stochastic control and reinforcement learning methods. Key to the representation is to represent the stochastic, nonlinear dynamics linearly onto a nonlinear feature space. We present a comprehensive framework to develop control and learning strategies that achieve efficiency, safety, robustness, and scalability with provable performance. We also show how the representation could be used to close the sim-to-real gap, to improve data efficiency in imitation learning, and to find localized policies efficiently for large-scale nonlinear network systems. Finally, if time permits, I will briefly present our recent work on training diffusion policy using online reinforcement learning for the policy representation.
Biography: Na Li is a Winokur Family Professor of Electrical Engineering and Applied Mathematics at Harvard University and a visiting researcher in Mitsubishi Electric Research Laboratories (MERL). She received her Bachelor's degree in Mathematics from Zhejiang University in 2007 and Ph.D. degree in Control and Dynamical Systems from California Institute of Technology in 2013. She was a postdoctoral associate at the Massachusetts Institute of Technology 2013-2014. She has held a variety of short-term visiting appointments including the Simons Institute for the Theory of Computing, MIT, and Google Brain. Her research lies in the control, learning, and optimization of dynamical systems, including theory development, algorithm design, and applications to real-world cyber-physical societal systems. She has been an associate editor for IEEE Transactions on Automatic Control, Systems & Control Letters, IEEE Control Systems Letters, and served on the organizing committee for a few conferences. She received the NSF career award, AFSOR Young Investigator Award, ONR Young Investigator Award, Donald P. Eckman Award, McDonald Mentoring Award, IFAC Distinguished Lecture, IFAC Manfred Thoma Medal, Ruberti Young Researcher Prize, along with other awards.
Host: Dr. Mihailo Jovanovic, mihailo@usc.edu
More Information: 2025.05.01 CSC Seminar - Na Li.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 248
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 Seminar: Dipankar Dasgupta
Tue, May 06, 2025 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dipankar Dasgupta, William Hill Professor in Cybersecurity | Director, Center for Information Assurance (CflA) | University of Memphis
Talk Title: Generic LLMs in Cybersecurity
Abstract: Generic Large Language Models (GLLMs) are continuously being released with increased size and capabilities, promoting the abilities of these tools as universal problem solvers. While the reliability of GLLMs' responses is questionable in many situations, these are augmented/ retrofitted with external resources for different applications including cybersecurity.
The talk will discuss major security concerns of these pre-trained models: first GLLMs are prone to adversarial manipulation such as model poisoning, reverse engineering and side-channel cyberattacks. Second, the security issues related to LLM-generated codes using open-source libraries/codelets for software development can involve software supply chain attacks. These may result in information disclosure, access to restricted resources, privilege escalation, and complete system takeover.
This talk will also cover the benefits and risks of using GLLMs in cybersecurity, particularly, in malware detection, log analysis, intrusion detection, etc. I will highlight the need for diverse AI approaches (non-LLM-based smaller models) trained with application-specific curated data, fine-tuned for well-tested security functionalities in identifying and mitigating emerging cyber threats including zero-day attacks.
Biography: Dr. Dipankar Dasgupta is a Professor of Computer Science at the University of Memphis since January 1997. He has extensively worked on the applications of bio-inspired and machine learning approaches to cyber defense. His groundbreaking works, including digital immunity, negative authentication, cloud insurance model, and auth-spectrum, have earned recognition in Computer World Magazine and other media outlets. He received research funding from different federal agencies including NSF, DARPA, IARPA, NSA, NAVY, ONR, DoD and DHS/FEMA. At the National Cyber Leap Year Summit in 2009, Dr. Dasgupta served as a Co-Chair for the Health-Inspired Network Defense working group (see the report, section 6, starting page 46), the results of which have led to a new research program within the Department of Homeland Security’s Science and Technology. With over 300 publications (including 4 patents), 22000+ citations, and an h-index of 68, Dr. Dasgupta's multidisciplinary research is highly acclaimed. He has received numerous awards, including the 2012 Willard R. Sparks Eminent Faculty Award and the 2014 ACM SIGEVO Impact Award. He also received five best paper awards in different international conferences and has organized Symposia on Computational Intelligence in Cyber Security at IEEE SSCI during 2007-2023. Dr. Dasgupta is an IEEE Fellow, AIIA Fellow and NAI Fellow, an ACM Distinguished Speaker (2015-2020), an IEEE Distinguished Lecturer (2022-2024) and 2024 NSF-Fulbright Distinguished Scholar. He regularly serves as a panelist and keynote speaker and offers tutorials in leading computer science conferences and has given more than 350 invited talks in different universities and industries.
Host: Viktor Prasanna, prasanna@usc.edu
More Information: 2025.05.06 ECE Seminar - Dipankar Dasgupta.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
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 Seminar: Naifeng Zhang
Fri, May 09, 2025 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Naifeng Zhang, PhD Candidate, Electrical and Computer Engineering, Carnegie Mellon University
Talk Title: Code generation for cryptographic kernels using multi-word modular arithmetic
Abstract: Fully homomorphic encryption (FHE) and zero-knowledge proofs (ZKPs) are emerging as solutions for data security in distributed environments. However, the widespread adoption of these encryption techniques is hindered by their significant computational overhead, primarily resulting from core cryptographic operations that involve large integer arithmetic. This paper presents a formalization of multi-word modular arithmetic (MoMA), which breaks down large bit-width integer arithmetic into operations on machine words. We further develop a rewrite system that implements MoMA through recursive rewriting of data types, designed for compatibility with compiler infrastructures and code generators. We evaluate MoMA by generating cryptographic kernels, including basic linear algebra subprogram (BLAS) operations and the number theoretic transform (NTT), targeting various GPUs. Our MoMA-based BLAS operations outperform state-of-the-art multi-precision libraries by orders of magnitude, and MoMA-based NTTs achieve near-ASIC performance on commodity GPUs.
Biography: Naifeng Zhang is a fourth-year Ph.D. candidate in Electrical and Computer Engineering at Carnegie Mellon University, advised by Professor Franz Franchetti. He received bachelor's degrees in Mathematics and Computer Science from the University of Southern California, advised by Professor Viktor K. Prasanna. His research interests include high-performance code generation, programming languages, compilers, and algorithms. His webpage can be found at https://naifeng.github.io/
Host: Dr. Viktor Prasanna, prasanna@usc.edu
More Information: 2025.05.09 ECE Seminar - Naifeng Zhang.pdf
Location: Michelson Center for Convergent Bioscience (MCB) - MCB 102
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 and Microelectronics Technology Seminar - Taro Hitosugi, Friday, May 16th at 1:30pm PST in EEB 248
Fri, May 16, 2025 @ 01:30 PM - 02:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Taro Hitosugi, Department of Chemistry, The University of Tokyo
Talk Title: Autonomous experiments for thin films and solid materials
Series: Semiconductors & Microelectronics Technology
Abstract: Autonomous experiments, integrating machine learning and robotics, are revolutionizing materials science research. This approach accelerates the discovery and optimization of novel materials by automating the experimental process and enabling the exploration of vast parameter spaces. We present an autonomous experimental system for thin-film materials research. This system automates all stages of the experimental process, including sample handling, thin-film deposition, optimization of growth conditions, and comprehensive data acquisition (X-ray diffraction, scanning electron microscope, Raman spectroscopy, etc.). By combining robotic control with Bayesian optimization, our system autonomously explores the parameter space and identifies optimal conditions. We demonstrate this approach by synthesizing and maximizing the electrical conductivity of Nb-doped TiO2 thin films. Furthermore, this autonomous system has enabled the discovery of new ionic conductors. This work highlights the potential of autonomous experimentation for accelerating materials science research, particularly for solid-state materials. We are currently developing an autonomous experimental system for synthesizing bulk materials.
Biography: Taro Hitosugi is a Professor of Chemistry at The University of Tokyo. He received his Ph.D. from The University of Tokyo in 1999 and began his career at Sony Corporation. In 2003, he transitioned to academia, holding positions as an Assistant Professor at The University of Tokyo and Associate Professor at Tohoku University before becoming a full professor at the Tokyo Institute of Technology in 2015. He returned to The University of Tokyo in 2022. An expert in solid-state chemistry, thin film, and surface and interface science, Professor Hitosugi's research focuses on materials for electronics and energy applications. His work includes the development of autonomous material synthesis using machine learning and robotics to accelerate materials science research. He has authored more than 200 peer-reviewed publications in leading academic journals. He serves on the editorial advisory board of APL Materials and as an associate editor for Science and Technology of Advanced Materials (STAM). Professor Hitosugi contributes his expertise to the Cabinet Office's "Materials Strategy" and the Science Council of Japan.
Host: Joshua Yang, Chongwu Zhou, Steve Cronin and Wei Wu
More Information: Taro Hitosugi_2024-05-16.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. -
AAI-CCI-MHI Seminar on CPS
Mon, May 19, 2025 @ 01:00 PM - 02:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Stephen Lee, Assistant Professor, University of Pittsburgh
Talk Title: Green by Design: Rethinking Computing for Sustainability
Abstract: In response to climate change, there is an urgent need to rethink how we design and operate computing systems to facilitate the transition to a low-carbon economy. While prior work has primarily focused on improving energy efficiency, in this talk, I will argue that reducing the carbon footprint of computing is equally important. By incorporating carbon-aware design as a first-class principle, we can not only minimize energy consumption but also significantly reduce emissions. This talk will highlight both the operational and embodied emissions of computing. I will begin by discussing how we can redesign serverless computing to be carbon-aware and optimize for emissions. I will also present strategies for integrating renewable energy into the design of computing systems. Furthermore, I will discuss the challenges associated with accounting for embodied emissions and propose potential solutions. The talk will conclude with opportunities to enhance carbon-aware systems beyond computing, into areas such as built environments.
Biography: Stephen Lee is an Assistant Professor at the University of Pittsburgh. His research area spans several areas of computer systems, including distributed systems and cyber-physical systems, with an emphasis on domains such as smart grids and buildings. He focuses on designing computing systems and developing learning-based methods for system design and optimization, in the context of sustainability and privacy. He has received numerous awards including Best Paper award at IEEE TPS 2024 and Best Runner-Up paper awards at IEEE TPS, ACM/IEEE ICCPS (2023), ACM Buildsys (2021), ACM e-Energy (2020). He has served on the technical program committee of ACM eEnergy, INFOCOM, PerCom, and IoTDI. Stephen received his Ph.D. from UMass Amherst, M.S. from Chennai Mathematical Institute, and B.S. from St. Stephen’s College Delhi.
Host: Bhaskar Krishnamachari
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Ariana Perez
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. -
Quantum/Physics Joint seminar - Ruslan Shaydulin, Monday, May 19th at 2pm in EEB 132 and Zoom
Mon, May 19, 2025 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Ruslan Shaydulin, JPMorgan Chase
Talk Title: Certified randomness using a trapped-ion quantum processor
Series: Quantum/Physics Joint Seminar Series
Abstract: Although quantum computers can perform a wide range of practically important tasks beyond the abilities of classical computers, realizing this potential remains a challenge. An example is to use an untrusted remote device to generate random bits that can be certified to contain a certain amount of entropy. Certified randomness has many applications but is impossible to achieve solely by classical computation. Here we demonstrate the generation of certifiably random bits using the 56-qubit Quantinuum H2-1 trapped-icon quantum computer accessed over the internet. Our protocol leverages the classical hardness of recent random circuit sampling demonstrations: a client generates quantum ‘challenge’ circuits using a small randomness seed, sends them to an untrusted quantum server to execute and verifies the results of the server. We analyze the security of our protocol against a restricted class of realistic near-term adversaries. Using classical verification with measured combined sustained performance of 1.1 x 1018 floating-point operations per second across multiple supercomputers, we certify 71,313 bits of entropy under this restricted adversary and additional assumptions. Our results demonstrate a step towards the practical applicability of present-day quantum computers. See paper for more details: [Nature 640, 343-348 (2025)]
Biography: Ruslan Shaydulin is Head of Quantum Engineering Research at the Global Technology Applied Research center at JPMorgan Chase, where he and his team focus on practical aspects of evaluating quantum algorithmic speedups and realizing them on hardware. Areas of responsibility of Ruslan’s team include numerical benchmarking of quantum algorithms, compilation and execution on quantum hardware, compilation to fault-tolerant architectures and error correction. Prior to joining JPMorgan Chase, Ruslan was a Maria Goeppert Mayer fellow at Argonne National Laboratory.
Host: Quntao Zhuang, Eli Levenson-Falk, Jonathan Habif, Daniel Lidar, Kelly Luo,k Todd Brun, Tony Levi, Stephan Haas
More Info: https://urldefense.com/v3/__https://usc.zoom.us/j/94114871670?pwd=aUuQQBPCNwcVa6n4PVaKPPFbmjB6Vv.1__;!!LIr3w8kk_Xxm!ukAXqVyGtAvUZVcXHe6nyHgbHKMDXHKFeICjv9Z-WkhGLtgec-ZSi4LhNLVq5_JpgBhdkPVexaNt_yCSLFrcu2_1sw$
More Information: Ruslan Shaydulin 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. -
ECE Seminar - Prof. Saif Khan Mohammed, Friday, May 30th at 10am in EEB 132
Fri, May 30, 2025 @ 10:00 AM - 11:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. Saif Khan Mohammed, EE - Indian Institute of Technology, Delhi, India
Talk Title: Zak-OTFS ⓠThe Waveform for Next Generation Communication Systems
Series: ECE Seminar
Abstract: In this talk we present our work based on signal representation in the delay-Doppler (DD) domain which gives rise to pulsones. The DD domain representation of any time-domain/frequency-domain signal is given by its Zak transform. Pulsones are simply quasi-periodic pulses in the DD domain whose interaction with a doubly-spread channel is stationary and non-fading when the pulse period along the delay axis is greater than the channel delay spread and the pulse period along the Doppler axis is greater than the channel Doppler spread, a condition we refer to as the crystallization condition. In Zak-OTFS modulation, information is carried by pulses in the DD domain. Due to the stationary input-output (I/O) relation of Zak-OTFS modulation, the effective DD domain channel can be acquired/estimated with negligible overhead, and the performance is robust to channel delay and Doppler spread.
Zak-OTFS modulation is therefore ideally suited for ubiquitous communication (e.g., satellite communication, aircraft communication, high speed train, where we encounter high Doppler spread). Machine learning (ML) can revolutionize wireless communication only if the interaction of the carrier waveforms with the channel varies very slowly in both time and frequency. Since Zak-OTFS renders a stationary I/O relation, it enables learning algorithms to achieve better resource allocation/precoding etc. Zak-OTFS waveforms are also suited for radar sensing. Appropriate DD domain signal processing allows for co-existence of communication and sensing signals with little cross-interference, i.e., integrated sensing and communication.
Our pioneering work on this new waveform is a paradigm shift in the way communication systems are designed and is expected to play a decisive role in the future of wireless communication. This work is presented in detail in our book titled “OTFS Modulation: Theory and Applications”, Wiley and IEEE Press, Nov. 2024.
Biography: Saif Khan Mohammed is a Professor with the Department of Electrical Engineering, Indian Institute of Technology Delhi (IIT Delhi). He currently holds the Jai Gupta Chair at IIT Delhi. He received the B.Tech. degree in Computer Science and Engineering from IIT Delhi, New Delhi, India, in 1998, and the Ph.D. degree from the Electrical Communication Engineering Department, Indian Institute of Science, Bangalore, India, in 2010. From 2010 to 2011, he was a Post-Doctoral Researcher at the Communication Systems Division (Commsys), Electrical Engineering Department (ISY), Linkoping University, Sweden. He was an Assistant Professor at Commsys, from September 2011 to February 2013. His main research interests include waveforms for sixth generation (6G) communication systems, wireless communication using large antenna arrays, coding and signal processing for wireless communication systems, information theory, and statistical signal processing.
Host: Andreas Molisch
More Info: https://usc.zoom.us/j/96943734400
More Information: 2025 Ming Hsieh ECE Seminar .pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: https://usc.zoom.us/j/96943734400
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.
