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Events for November 14, 2023
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ECE Seminar: Filter Banks on Arbitrary Graphs Using Generalized Laplacian Eigenvectors
Tue, Nov 14, 2023 @ 10:30 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Eduardo Pavez Carvelli, Postdoctoral Research Associate/Ming Hsieh Department of Electrical and Computer Engineering
Talk Title: Filter Banks on Arbitrary Graphs Using Generalized Laplacian Eigenvectors
Abstract: In the past decade, Graph Signal Processing (GSP) has become a popular framework to represent and process irregular and unstructured data, such as 3D point clouds arising from immersive communication and autonomous vehicle applications.
In this talk I will present our recent work on two channel filter banks for signals on graphs. Filter banks and other multi-resolution transformations have been extensively used for signal and image processing. Due to graph irregularities it can be challenging to construct filter banks for graphs, while satisfying desirable properties such as critical sampling, perfect reconstruction and low complexity. Bipartite filter banks are amongst the most popular designs satisfying these requirements, yet they are limited to bipartite graphs represented by their normalized Laplacian matrix. In practice graphs are rarely bipartite and other graph matrices are often preferred.
We substantially extend bipartite filter bank theory to arbitrary (non-bipartite) graphs and positive definite graph matrices. Our key insight is realizing the limitations of graph eigenvectors for spectral design of graph filter banks. As an alternative, we propose to use Q-orthogonal generalized eigenvectors of graphs, which can be constructed with certain spectral symmetries that can be exploited for filter bank design. The proposed graph filter banks are applied to graphs constructed on 3D point clouds with hundreds of thousands of nodes.
Biography: Eduardo Pavez Carvelli received the B.S. and M.Sc. degrees in electrical engineering from the University of Chile, Santiago, Chile, in 2011 and 2013, respectively, and the Ph.D. degree in electrical engineering from the University of Southern California, in 2019. He was an intern at Microsoft Research, and Mitsubishi Electric Research Laboratories, and he is currently a Postdoctoral Research Associate at the University of Southern California. His research is in the areas of graph signal processing, 3D point cloud processing and compression. His work on point cloud and video compression received best paper awards at IEEE ICIP 2020 and 2022.
Host: Dr. Richard M. Leahy, leahy@usc.edu
Webcast: https://usc.zoom.us/j/95889271695?pwd=TDFRWEsyY1VMWEFFQmZTdkg4ODhYQT09Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
WebCast Link: https://usc.zoom.us/j/95889271695?pwd=TDFRWEsyY1VMWEFFQmZTdkg4ODhYQT09
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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ECE Seminar: Reinforcement Learning for Control and Beyond
Tue, Nov 14, 2023 @ 12:00 PM - 01:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Jay H. Lee, C. H. Cho Professor of Mork Family Department of Chemical Engineering and Materials Science University of Southern California
Talk Title: Reinforcement Learning for Control and Beyond
Abstract: Since Alan Turing’s remarkable foresight of creating a machine that simulates the “adult brain” starting from the “child mind” through a computer algorithm that educates through rewards and punishments, reinforcement learning (RL) has been at the forefront of many academic fields including psychology, computer science, and control. With recent advancement of deep learning and GPU-computing as well as well-publicized success stories like the Alpha-Go, it is enjoying a renaissance of popularity and offers opportunities for applications with commercial impacts. RL and control originated from the different fields but they both address the same basic problem of making sequential decisions in an uncertain, dynamic environment to maximize/minimize a long-term objective function. In this presentation, similarities and differences between reinforcement learning and optimal control will be brought to attention and some ideas will be shared on how they can be brought to complement and support each other in solving complex industrial decision problems. Some exemplary applications expected to benefit significantly from the use of RL concepts and methods will be presented, including batch process control, energy planning, and materials design.I will also give a short introduction to other research topics I am currently engaged in, including lithium-ion battery’s state of health prediction and evaluation of CO2 capture, utilization, and storage (CCUS) technologies.
Biography: Jay H. Lee obtained his B.S. degree in Chemical Engineering from the University of Washington, Seattle, in 1986, and his Ph.D. degree in Chemical Engineering from California Institute of Technology, Pasadena, in 1991. From 1991 to 1998, he was with the Department of Chemical Engineering at Auburn University, AL, as an Assistant Professor and an Associate Professor. From 1998-2000, he was with School of Chemical Engineering at Purdue University, West Lafayette, and then with the School of Chemical Engineering at Georgia Institute of Technology, Atlanta from 2000-2010 and Chemical and Biomolecular Engineering Department at Korea Advanced Institute of Science and Technology (KAIST) from 2010-2022, where he was the department head from 2010-2015, Associate VP of International Relations from 2015-2017, KEPCO Chair Professor and the founding Director of Saud Aramco-KAIST CO2 Management Center at KAIST. He is currently C. H. Cho Chair Professor of Mork Family Department of Chemical Engineering and Materials Science at University of Southern California. He was a recipient of the National Science Foundation’s Young Investigator Award in 1993 and was elected as an IEEE Fellow and an IFAC (International Federation of Automatic Control) Fellow in 2011 and an AIChE Fellow in 2013. He was also the recipient of the 2013 Computing in Chemical Engineering Award given by the AIChE’s CAST Division and the 2016 Roger Sargent Lecturer at Imperial College, UK. He is an Editor of Computers and Chemical Engineering and Discover Chemical Engineering. He was currently the Editor-in-Chief of Korean Journal of Chemical Engineering and also the chair of IFAC Coordinating Committee on Process and Power Systems. He published over 260 manuscripts in SCI journals with ~21000 Google Scholar citations. His research interests are in the areas of system identification, state estimation, robust control, model predictive control, and reinforcement learning with applications to sustainable energy systems, bio-refinery, and CO2 capture/conversion systems.
Host: Dr. Richard M. Leahy, leahy@usc.edu
Webcast: https://usc.zoom.us/j/93773325275?pwd=V3R4aEg1cW9DU1AvT3RCcHArS3RWUT09More Information: ECE-Seminar-Lee-111423.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
WebCast Link: https://usc.zoom.us/j/93773325275?pwd=V3R4aEg1cW9DU1AvT3RCcHArS3RWUT09
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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DREAM Industry Mentorship speaker series
Tue, Nov 14, 2023 @ 12:30 PM - 01:30 PM
USC Viterbi School of Engineering
University Calendar
DREAM (Direct Response to Engineers Aspirations from Mentors) connects students with high profile industry professionals from a variety of tech and destination companies who help them create a vision for their futures, align their careers around purpose, and build character in the context of growth, reinvention, and constant change. Industry mentors discuss how professional challenges present opportunities for character and leadership development. This event will feature USC Marshall alumni George Jacobs, CEO and founder of venture backed start-up Accelerate, in conversation with Vishal Lugani, VC and founding partner at Acrew Capital, about their journeys through entrepreneurial challenges and the evolving landscape of tech.
Location: Ronald Tutor Hall of Engineering (RTH) - 105
Audiences: Everyone Is Invited
Contact: Elisabeth Arnold Weiss
Event Link: https://cglink.me/2nB/r392961
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Epstein Institute, ISE 651 Seminar Class
Tue, Nov 14, 2023 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Chai Keong Toh, ITS Senior Fellow, Berkeley Institute of Transportation Studies, University of California, Berkeley
Talk Title: Smart Cities: Design & Research
Host: Dr. Neil Siegel
More Information: November 14, 2023.pdf
Location: Social Sciences Building (SOS) - SOS Building, B2
Audiences: Everyone Is Invited
Contact: Grace Owh
