Conferences, Lectures, & Seminars
Events for August
-
Quantum Science & Technology Seminar - Xun Gao, Thursday, August 15th at 11am in EEB 248
Thu, Aug 15, 2024 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Xun Gao, University of Colorado Boulder
Talk Title: Interpretable Quantum Advantage in Neural Sequence Learning
Series: Quantum Science & Technology Seminar Series
Abstract: Quantum neural networks have been widely studied in recent years due to their potential practical utility and recent results showing their ability to efficiently express certain classical data. However, analytic results to date rely on assumptions and arguments from complexity theory. As a result, there is little intuition regarding the source of the expressive power of quantum neural networks or for which classes of classical data any advantage can be reasonably expected to hold. In this study, we examine the relative expressive power between a broad class of neural network sequence models and a class of recurrent models based on quantum mechanics. We demonstrate that quantum contextuality is the source of an unconditional memory separation in the expressivity of the two model classes. Using this intuition, we study the relative performance of our introduced model on a standard translation dataset exhibiting linguistic contextuality. Our quantum models outperform state-of-the-art classical models, even in practice. Finally, I will briefly discuss future directions of quantum neural networks and their potential connections to concepts in condensed matter physics, such as Berry phase and spin glass.
Biography: Xun Gao is an assistant professor at University of Colorado Boulder and an associate fellow at JILA. He got his PhD from Tsinghua University under the supervision of Luming Duan. Then he was a postdoc at Harvard University from Mikhail Lilian's group. His research interests are quantum computational advantage and quantum machine learning.
Host: Quntao Zhang, Wade Hsu, Mengjie Yu, Jonathan Habif & Eli Levenson-Falk
More Information: Xun Gao 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. -
AAI-CCI-MHI Seminar on CPS
Wed, Aug 28, 2024 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Sonia Roberts, Assistant Professor Wesleyan University
Talk Title: From legged robots to knitted ones
Series: EE598 Seminar Series
Abstract: Traditional robotics assumes rigid bodies interacting with rigid environments. However, the real world is soft. Robots will need to be able to move over materials like sand, snow, and leaf litter, and will need to be able to interact with fruits, fabrics, and of course humans. I will discuss two types of soft interactions between a robot and the world: Robot locomotion on granular media, and the use of knitting as a computational fabrication method to create soft sensors for robots.
Biography: Dr. Sonia Roberts is an Assistant Professor of Computer Science at Wesleyan University working on knitted sensors for soft robot skins and legged robot locomotion on granular media. In 2023, she completed a postdoc with Prof. Kris Dorsey at Northeastern as part of the Institute for Experiential Robotics, where she worked on soft origami sensors. She received her PhD in Electrical and Systems Engineering from the University of Pennsylvania in 2021, where she worked with Prof. Dan Koditschek in the GRASP Lab to develop a reactive controller to reduce the energetic cost of transport for legged robots on sand. Prior to coming to Penn, Sonia worked at Janelia Farm Research Campus on a team building a rough behavioral map of the fruit fly brain, and with John Long using evolutionary robotics tools to answer biological questions at Vassar College.
Host: Feifei Qian
More Information: AAI-CCI-MHI Seminar on CPS Sonia Roberts.pdf
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. -
Semiconductors & Microelectronics Technology Seminar - John Paul Strachan, Thursday, Aug. 29th at 2pm in EEB 248
Thu, Aug 29, 2024 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: John Paul Strachan, Peter Grünberg Institute (PGI-14), Forschungszentrum Jülich, Jülich, Germany RWTH Aachen University, Aachen, Germany
Talk Title: Engineering memristor-CMOS based neuromorphic architectures for computational acceleration: NP-hard optimization problem solvers and building associative memories
Series: Semiconductors & Microelectronics Technology
Abstract: There is simultaneously an interest for more energy-efficient hardware in challenging applications, as well as a drive to overhaul the von Neumann architecture toward more brain-like architectures. I will describe our in-memory approach that applies to both these two topic areas, especially where emerging memories like memristors can be utilized with traditional CMOS in new circuits and architectures. Such hybrid circuits can yield challenges in variability, offer many benefits. I will discuss our modified Hopfield neural network accelerator for challenging optimization problem classes such as Boolean satisfiability (3-SAT), showing performance comparisons to competing approaches with both mature and emerging technologies. In complementary work, we build new architectures around content addressable memories (CAM), which offer a highly parallel pattern look-up capability. Designs are improved utilizing non-volatile and analog memristive devices for higher data density and lower energy than CMOS-only counterparts. We utilize such circuits in a variety of associative computing applications, including security, genomics, and machine learning. Going further, we are interested in how learning can be incorporated into such memory circuits and we describe a modified "differentiable" CAM circuit that is compatible with gradient-based training algorithms and illustrate some applications of such a circuit.
Biography: John Paul Strachan directs the Peter Grünberg Institute on Neuromorphic Compute Nodes (PGI-14) at Forschungszentrum Jülich and is a Professor at RWTH Aachen. Previously he led the Emerging Accelerators team as a Distinguished Technologist at Hewlett Packard Labs, HPE. His teams explore novel types of hardware accelerators using emerging device technologies, with expertise spanning materials, device physics, circuits, architectures, benchmarking and building prototype systems. Their interests span applications in machine learning, network security, and optimization. John Paul has degrees in physics and electrical engineering from MIT and a PhD in applied physics from Stanford University. He has over 60 patents, has authored or co-authored over 100 peer-reviewed papers, and been the PI in many USG research grants. He has previously worked on nanomagnetic devices for memory for which he was awarded the Falicov Award from the American Vacuum Society, and has developed sensing systems for precision agriculture in a company which he co-founded. He serves in professional societies including IEEE IEDM ExComm, the Nanotechnology Council ExComm, and past program chair and steering member of the International Conference on Rebooting Computing.
Host: J Yang, H Wang, C Zhou, S Cronin, W Wu
More Information: John Paul Strachan_2024-08-29.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.
