Conferences, Lectures, & Seminars
Events for December
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ECE Seminar: Biologically Inspired Algorithm and Hardware Co-Design for Efficient Machine Intelligence
Wed, Dec 04, 2024 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Priya Panda, Assistant Professor, Electrical & Computer Engineering Department, Yale University
Talk Title: Biologically Inspired Algorithm and Hardware Co-Design for Efficient Machine Intelligence
Abstract: Artificial Intelligence (AI) is poised to revolutionize society, yet its escalating energy demands pose a formidable challenge to its long-term sustainability. The staggering gap in energy consumption between biological (Human Brain @20watts) and artificial intelligence (ChatGPT @100KWatts) is striking. My research aims to bridge this gap with a bio-inspired, integrative approach, where algorithm-hardware co-design and neuromorphic computing converge to create intelligent, energy-efficient systems. In this talk, I will talk about my group’s recent efforts towards enabling and democratizing spike-based machine intelligence design, simulation, and evaluation across different applications. I’ll explore the distinctive benefits of Spiking Neural Networks (SNNs), especially the use of temporal dynamics, which enhances robustness while offering significant gains in latency, energy efficiency, and accuracy in tasks like video segmentation, human activity recognition, and event sensing. From a hardware perspective, I’ll examine how memory and sparsity management can accelerate SNNs on general-purpose platforms, introducing techniques like input-aware dynamic temporal exit and scaling-free quantization for efficient weight and activation compression. Finally, I will share a vision for the future of energy-efficient AI, where our ongoing efforts in input-aware adaptive computation for large foundation models hold promise for developing end-to-end edge cloud intelligent systems capable of visual, language and multi-faceted visual-language processing. This approach opens the door to deploying low-power embodied AI and robotics.
Biography: Priya Panda is an assistant professor in the Electrical & Computer Engineering department at Yale University, USA and a Visiting Faculty Researcher at Google DeepMind with the vision and compilers/architectures team. She received her B.E. and Master's degree from BITS, Pilani, India in 2013 and her Ph.D. from Purdue University, USA in 2019. During her PhD, she interned in Intel Labs where she developed large scale spiking neural network algorithms for benchmarking the Loihi chip. She is the recipient of the 2019 Amazon Research Award, 2022 Google Research Scholar Award, 2022 DARPA Riser Award, 2023 NSF CAREER Award, 2023 DARPA Young Faculty Award, and the inaugural 2024 Purdue Engineering 38 under 38 award. She has also received the 2022 ISLPED Best Paper Award, 2022 IEEE Brain Community Best Paper Award and 2024 ASP-DAC Best Paper Nomination. Her research interests lie in Spiking Neural Networks, Efficient AI algorithm and hardware design.
Host: Dr. Peter Beerel, pabeerel@usc.edu
Webcast: https://usc.zoom.us/j/96755228104?pwd=NR5BYktbr3Yw36DWAtj5cakkt1qQR0.1 (USC NetID login required)Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
WebCast Link: https://usc.zoom.us/j/96755228104?pwd=NR5BYktbr3Yw36DWAtj5cakkt1qQR0.1 (USC NetID login required)
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. -
PhD Defense
Fri, Dec 06, 2024 @ 10:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Talk Title: Efficient and Accurate 3D FISP=MRF at 0.55 T
Abstract: Magnetic Resonance Fingerprinting (MRF) are a set of popular multiparametric quantitative MRI techniques. With the resurgence of interest in mid- and low-field MRI, such as the 0.55 T MR system in Dynamic Imaging Science Center in USC, these techniques have gained growing research and clinical tractions. At 0.55 T, a basic fast imaging with steady-state free precession (FISP)-MRF approach has been shown feasible with promising but unexplored improvements, however, also with substantial quantification biases from reference measurements and literature values. Therefore, how to perform this approach in a more Signal-to-Noise Ratio(SNR) efficiency optimized way and how to improve its quantification accuracy have become interesting research problems.
In this dissertation, I propose a more efficient and accuracy FISP-MRF approach at 0.55 T. I start with improving 0.55 T FISP-MRF SNR efficiency and the approach produces more precise results (up to 50% smaller standard deviation values) but temporarily with unaddressed biases. It includes higher readout duty cycle, constrained reconstruction and artifacts mitigation algorithms. Then, I focus on refining RF excitation designs, which helps to partially suppress the sources of bias, resulting in more accurate quantification (~75% less bias).
Biography: Zhibo Zhu is a PhD candidate in Electrical and Computer Engineering in University of Southern California, advised by Prof. Krishna S. Nayak. He received Bachelor of Science degree in Nanjing University of Post and Telecommunication in 2015 and Master of Science degree in University of Southern California in 2017. His current research interest is improved FISP-MRF at 0.55 T MRI.
Host: Krishna Nayak
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Bella Schilter
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 - Physics Joint Seminar Series, Mark Saffman, Friday, Dec. 6th at 2pm in SSL 202
Fri, Dec 06, 2024 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Mark Saffman, Department of Physics, University of Wisconsin-Madison
Talk Title: Gate Model Quantum Computing with Atom Arrays
Series: MHI Physics Joint Seminar Series
Abstract: Quantum computing with neutral atom qubits has advanced rapidly with the development of large 2D arrays and high-fidelity entangling gates. We have used atomic qubits for a variational simulation of the Lipkin-Meshkov-Glick model incorporating noise mitigation techniques. The talk will provide an overview of architectural options for neutral atom qubit arrays and present new approaches for implementing nonlocal QEC codes and fast measurements, as well as progress towards photonic remote entanglement.
Biography: Mark Saffman is an experimental physicist working in the areas of atomic physics, quantum and nonlinear optics, and quantum information processing. His research team was the first to demonstrate a quantum CNOT gate for the deterministic entanglement of a pair of neutral atoms. This was done using dipole mediated interactions between highly excited Rydberg atoms. He is currently developing scalable arrays of neutral atoms for quantum computation, communication, and sensing applications. He is the Johannes Rydberg Professor of Physics at the University of Wisconsin-Madison and has been recognized with an Alfred P. Sloan fellowship, a Vilas Associate Award, the WARF Innovation Award, and is a fellow of the American Physical Society, and Optica. He has been active in professional service including two decades as an Associate Editor at the Physical Review and is the director of The Wisconsin Quantum Institute. He also serves as Chief Scientist for Quantum Information at Infleqtion, Inc.
Host: Quntao Zhuang, Eli Levinson-Falk, Jonathan Habif, Daniel Lidar, Kelly Luo, Todd Brun, Tony Levi, Stephan Haas
More Info: https://usc.zoom.us/j/92584409725
More Information: Mark Saffman -Dec 6.pdf
Location: Seaver Science Library (SSL) - 202
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: https://usc.zoom.us/j/92584409725
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 - Dr. Alyosha Molnar, Friday, December 6th at 2pm in EEB 248
Fri, Dec 06, 2024 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Alyosha Molnar, Professor, Cornell University
Talk Title: Analog at the Extremes: Circuits from the Edge
Series: Integrated Systems
Abstract: For at least 3 decades techno-polemicists have been predicting the end of analog circuits, even as the field has exploded both commercially and academically. What is true, however, is that analog circuits have changed, as digital computation and analog-to-digital converters have improved by leaps and bounds, pushing many traditionally analog problems into the digital, and even software domain. Some problems, however, remain beyond the reach of purely digital solutions. These problems are characterized by either extremely constrained power and size, or by very high frequency, very high dynamic range requirements. At the same time, such circuits must be designed with a much more algorithm-aware mindset, as they rarely exist in a computation-free environment. I will discuss two examples of such circuits. The first example is a tiny (60um x 300um) neural implant, able to measure and transduce electrophysiological signals from neurons and transmit them wirelessly. These microscale optoelectronically transduced electrodes (MOTEs) can be entirely powered by light (from a 2-photon imaging setup, for example), at levels safe for the brain, while reporting both spiking and synaptic activity in-vivo. The second problem is high dynamic-range RF and mm-Wave receivers. I will discuss our work in N-path mixers and filters which have been shown to enable flexible, interference tolerant receivers, and discuss our recent work mapping N-path designs to mmWave frequencies, while maintaining the mixers' linearity and noise without burning excessive power. I will finish up by discussing of a new style of flexible receiver, which leverages circuit and algorithm co-design to generate diverse combinations of signal and interference artifact. These diverse channels then allow simple algorithms to identification and remove interference artifacts without prior knowledge of the interference itself.
Biography: Alyosha Molnar received his B.S. in Engineering from Swarthmore College and his Ph.D. in Electrical Engineering from UC Berkeley. At Conexant Systems (1998-2002), he co-led the development of the first commercially successful cellular direct conversion receiver and fully integrated quad-band GSM transceiver. Currently the Ilda and Charles Lee Professor of Engineering at Cornell University, his research encompasses RF and mmWave integrated circuits, novel image sensors and processing, neural interface systems, and microscale autonomous systems. His graduate work included pioneering sub-milliwatt radios for "smart dust" and studying biological circuits in the mammalian retina. Since joining Cornell in 2007, his contributions have been recognized with several prestigious honors including the NSF CAREER Award, DARPA Young Faculty Award, ISSCC Lewis Winner Award, and the Darlington Best Paper Award.
Host: MHI - ISSS, Hashemi, Chen and Sideris
More Info: https://usc.zoom.us/j/93310952640
More Information: MHI_Seminar_Flyer_Molnar_Dec6_2024.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: https://usc.zoom.us/j/93310952640
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. -
World models beyond autoregressive next state prediction
Mon, Dec 09, 2024 @ 03:00 PM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering, Thomas Lord Department of Computer Science, USC School of Advanced Computing
Conferences, Lectures, & Seminars
Speaker: Abhishek Gupta, Ph.D., Assistant Professor of Computer Science and Engineering, Paul G. Allen School at the University of Washington
Talk Title: World models beyond autoregressive next state prediction
Series: CSC@USC/CommNetS-MHI Seminar Series
Abstract: Learned models of system dynamics provide an appealing way of predicting the future outcomes in a system, enabling downstream usage for planning or off-policy evaluation in applications such as robotics. However, the prevalent paradigm of autoregressive, next-state prediction in learning dynamics models is challenging to scale to environments with high dimensional observations and long horizons. In this talk, I will present alternative techniques for model learning that go beyond directly predicting next states. Firstly, we will discuss a reconstruction-free class of models that go beyond next-observation prediction by learning the evolution of task-directed latent representations for high dimensional observation spaces. We will then show how this can be generalized to learning a new class of models that avoid autoregressive prediction altogether by directly modeling long-term cumulative outcomes, while remaining task agnostic. In doing so, this talk will propose alternative ways of thinking about model learning that retain the benefits of transferability and efficiency from model-based RL, while going beyond next-state prediction.
Biography: Abhishek Gupta is an assistant professor of computer science and engineering at the Paul G. Allen School at the University of Washington. Prior to joining University of Washington, he was a post-doctoral scholar at MIT, collaborating with Russ Tedrake and Pulkit Agarwal. He completed his Ph.D. at UC Berkeley working with Pieter Abbeel and Sergey Levine, building systems that can leverage reinforcement learning algorithms to solve robotics problems. He is interested in research directions that enable directly performing reinforcement learning directly in the real world — reward supervision in reinforcement learning, large scale real world data collection, learning from demonstrations, and multi-task reinforcement learning. He has also spent time at Google Brain. He is a recipient of the NDSEG and NSF graduate research fellowships, and several of his works have been presented as spotlight presentations at top-tier machine learning and robotics conferences.
Host: Erdem Biyik
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Erdem Biyik
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 - Physics Joint Seminar Series - Daniel Sank, Tuesday, December 10th at 2pm in EEB 248 & Zoom
Tue, Dec 10, 2024 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Daniel Sank, Quantum AI, Google
Talk Title: Fast and Orderly Decoherence: A Systems Engineering View of Superconducting Qubit Readout and Reset
Series: MHI Physics Joint Seminar Series
Abstract: This presentation is a systems engineer's look at the superconducting qubit system, with focus on the two parts where we need fast and orderly decoherence: readout and reset. We introduce the basic theory of operation of the transmon qubit with focus on readout and reset and discuss the constraints placed by these operations on the off-chip physical apparatus, including package, wiring, cryostat, and the control electronics. Then, we give an in-depth tour of the mechanism, known as Measurement Induced State Transitions (MIST), through which the readout process kicks the qubit out of the computational subspace and into so-called "leakage states" which are poisonous for quantum error correction. Finally, we bring everything together to show how we design devices to respect the constraints introduced by readout and reset while still performing with sufficient speed and accuracy to support quantum error correction.
Host: Quntao Zhuang, Eli Levinson-Falk, Jonathan Habif, Daniel Lidar, Kelly Luo, Todd Brun, Tony Levi, Stephan Haas
More Info: https://usc.zoom.us/j/92584409725
More Information: Daniel Sank -Dec 10.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: https://usc.zoom.us/j/92584409725
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 - Physics Joint Seminar Series - Karan Mehta, Friday, December 13th at 2pm in SSL 202
Fri, Dec 13, 2024 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Karan Mehta, Electrical and Computer Engineering, Cornell University
Talk Title: Enhanced Trapped-Ion Quantum Control with Integrated Photonics
Series: MHI Physics Joint Seminar Series
Abstract: Practical quantum information processing requires significant advances over current systems in error and robustness of basic operations, and in scale. Despite the fundamental promise of trapped atomic ion qubits, the optics required pose a major challenge in scaling. Interfacing low-noise atomic qubits with scalable integrated photonics [1] offers a route to scale, enabling extensibility while simultaneously lending robustness to noise in sensitive quantum operations [2]. Beyond scaling, though, such techniques further allow generation of optical field profiles enabling improvements to coherent and incoherent processes [3]. I will discuss modeling work from our group predicting substantially increased cooling rates as well as motional mode bandwidths for ground-state laser cooling in structured light fields [4], routes to quantum logic leveraging related ideas, and early results from recent foundry-fabricated trap devices with fully integrated delivery to realize these schemes. I will also touch on challenges and opportunities for novel photonic materials and devices motivated by atomic quantum systems. [1] K.K. Mehta, C.D. Bruzewicz, R. McConnell, R.J. Ram, J.M. Sage, and J. Chiaverini. "Integrated optical addressing of an ion qubit." Nature Nanotechnology 11, 1066-1070 (2016). [2] K.K. Mehta, C. Zhang, M. Malinowski, T.-L. Nguyen, M. Stadler, and J.P. Home. "Integrated optical multi-ion quantum logic." Nature 586, 533-537 (2020). [3] A. Ricci Vasquez, et al. "Control of an atomic quadrupole transition in a phase-stable standing wave." PRL 130, 133201 (2023). [4] Z. Xing and K.K. Mehta. "Trapped-ion laser cooling in structured light fields." arXiv: 2411.08844 (2024).
Biography: Karan Mehta received BS. Degrees from UCLA in Electrical Engineering and Physics in 2010 and completed his PhD in Electrical Engineering and Computer Science at MIT in 2017, with the support of a DOE Science Graduate Fellowship. From 2017 to 2021 he was an ETH Postdoctoral Fellow and subsequently senior scientist at ETH Zurich. He joined Cornell ECE in January of 2022 where he leads the Photonics and Quantum Electronics group. He is recipient of an NSF CAREER award and a Sloan Research Fellowship in Physics.
Host: Quntao Zhuang, Eli Levinson-Falk, Jonathan Habif, Daniel Lidar, Kelly Luo, Todd Brun, Tony Levi, Stephan Haas
More Information: Karan Mehta -Dec. 13.pdf
Location: Seaver Science Library (SSL) - 202
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.
