Events for the 3rd week of September
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ECE Seminar
Wed, Sep 14, 2022 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Rodney Van Meter, Professor / Keio University
Talk Title: A Quantum Internet Architecture
Abstract: Entangled quantum communication is advancing rapidly, with laboratory and metropolitan testbeds under development, but to date there is no unifying Quantum Internet architecture. We propose a Quantum Internet architecture centered around the Quantum Recursive Network Architecture (QRNA), using RuleSet-based connections established using a two-pass connection setup. Scalability and internetworking (for both technological and administrative boundaries) are achieved using recursion in naming and connection control. In the near term, this architecture will support end-to-end, two-party entanglement on minimal hardware, and it will extend smoothly to multi-party entanglement and the use of quantum error correction on advanced hardware in the future. For a network internal gateway protocol, we recommend (but do not require) qDijkstra with seconds per Bell pair as link cost for routing; the external gateway protocol is designed to build recursively. The strength of our architecture is shown by assessing extensibility and demonstrating how robust protocol operation can be confirmed using the RuleSet paradigm.
Biography: Rodney Van Meter received a B.S. in engineering and applied science from the California Institute of Technology in 1986, an M.S. in computer engineering from the University of Southern California in 1991, and a Ph.D. in computer science from Keio University in 2006. His current research centers on quantum computer architecture, quantum networking and quantum education. He is the author of the book _Quantum Networking_. Other research interests include storage systems, networking, and post-Moore's Law computer architecture. He is now a Professor of Environment and Information Studies at Keio University's Shonan Fujisawa Campus. He is the Vice Center Chair of Keio's Quantum Computing Center, co-chair of the Quantum Internet
Research Group, a leader of the Quantum Internet Task Force, and a board member of the WIDE Project. Dr. Van Meter is a member of AAAS, ACM, APS, and IEEE. He is currently Editor in Chief of IEEE Transactions on Quantum Engineering, but this talk is 100% personal opinions.
Host: Todd Brun
Webcast: https://usc.zoom.us/j/92417517950?pwd=WUkycy90cndVQko5R3RhQ1U3STBDdz09Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
WebCast Link: https://usc.zoom.us/j/92417517950?pwd=WUkycy90cndVQko5R3RhQ1U3STBDdz09
Audiences: Everyone Is Invited
Contact: Corine Wong
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Center of Autonomy and AI, Center for Cyber-Physical Systems and the Internet of Things, and Ming Hsieh Institute Seminar Series
Wed, Sep 14, 2022 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Bharadwaj Satchidanandan, Massachusetts Institute of Technology
Talk Title: Mechanism Design for Next-Generation Electricity Markets
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: The power system is on the cusp of a revolution. The coming decade could witness increased renewable energy penetration, Electric Vehicle (EV) penetration, EV energy storage integration, demand response programs, etc. These changes have a profound impact on electricity market operations. New mechanisms must be devised to address a variety of important problems that are anticipated to arise in next-generation electricity markets. Most of the existing mechanism design settings are insufficient to model certain crucial features of these problems. To address this, we introduce the setting of Two-Stage Repeated Stochastic Games using which many problems that arise in the context of electricity markets can be readily modeled. We then present a mechanism for two-stage repeated stochastic games that implements truth-telling as a Dominant Strategy Non-Bankrupting Equilibrium --- a new notion of equilibrium that we have introduced for games. The mechanism also guarantees individual rationality and maximizes social welfare.
Biography: Bharadwaj Satchidanandan is a postdoctoral researcher at Massachusetts Institute of Technology where he is advised by Prof. Munther Dahleh. He received his Ph.D. in 2019 from Texas A&M University where he was advised by Prof. P. R. Kumar. His research interests include cyber-physical systems, security, renewable energy, mechanism design, game theory, etc.
Host: Pierluigi Nuzzo, nuzzo@usc.edu
Webcast: https://usc.zoom.us/j/98083929768?pwd=SUJreHk0N0ZXbk5QZ1ZPUkRlM3FmZz09Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
WebCast Link: https://usc.zoom.us/j/98083929768?pwd=SUJreHk0N0ZXbk5QZ1ZPUkRlM3FmZz09
Audiences: Everyone Is Invited
Contact: Talyia White
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Medical Imaging Seminar Series
Fri, Sep 16, 2022 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Yunsong Liu, Electrical and Computer Engineering, University of Southern California
Talk Title: Optimization Methods and Algorithms for Constrained Magnetic Resonance Imaging
Series: Medical Imaging Seminar Series
Abstract: Constrained MRI methods have shown great potential to improve the well-known trade-offs that exist in MRI between data acquisition time, signal-to-noise-ratio, and spatial resolution. In constrained MRI, we utilize prior information about the characteristics of the underlying MRI images to perform data acquisition, image reconstruction, and image analysis tasks more efficiently. This approach generally requires the use of mathematical optimization techniques, although the optimization problems are often challenging to solve efficiently due to their large-scale and non-trivial structure.
In this presentation, I will discuss three novel contributions I have made to mathematical optimization for constrained MRI. First, I will discuss work that utilizes phase constraints to accelerate MRI data acquisition based on non-Fourier radiofrequency encoding. While phase constraints are used classically in MRI, we believe that this is the first time that phase constraints are being applied to enable acceleration along a non-Fourier encoded spatial dimension. We make the novel observation that phase constraints can indeed be successfully used to reduce the number of required non-Fourier encodings, although this requires careful design of the non-Fourier encoding scheme. Results are presented in the context of gSlider, an acquisition method designed for highly-efficient high-resolution diffusion MRI. Second, we will describe a new algorithm we have developed that is designed for the separate regularization of magnitude and phase in MRI reconstruction problems. Our approach is based on a novel application of the proximal alternating linearized minimization algorithm (PALM), and incorporates additional novel features (i.e., Nesterov's momentum and independent selection of the step sizes for each coordinate) to increase convergence speed. Depending on the application, our proposed algorithm can be hundreds of times faster than existing algorithms for this problem. Finally, we will describe a novel algorithm that we have developed for spatial-spectral partial volume compartment mapping with applications to multicomponent diffusion and relaxation MRI. Our proposed algorithm is based on a novel application of the linearized alternating directions method of multipliers (LADMM) approach that takes advantage of the special structure of the inverse problem, and depending on the dataset, can achieve up to 5-fold acceleration compared to previous algorithms for this problem.
Biography: Yunsong Liu is a PhD candidate in Electrical and Computer Engineering at University of Southern California, supervised by Prof. Justin Haldar. He obtained his Bachelor's and Master's degree in Electrical Engineering at Xiamen University, China. He then spent half a year working on structured matrix recovery in Math Department at Hong Kong University of Science and Technology before joining Prof. Haldar's group at USC. His research has been focused on signal processing and optimization with applications in MRI.
Host: Justin Haldar, jhaldar@usc.edu
Webcast: https://usc.zoom.us/j/92068313291?pwd=MnlVUTJrWkRpUVdQYU04S2t4cUVjZz09Location: Online
WebCast Link: https://usc.zoom.us/j/92068313291?pwd=MnlVUTJrWkRpUVdQYU04S2t4cUVjZz09
Audiences: Everyone Is Invited
Contact: Talyia White
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ECE-EP Seminar - Dr. Kaiyuan Yang, Friday, September 16th at 2pm in EEB 248
Fri, Sep 16, 2022 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Kaiyuan Yang, Rice University
Talk Title: Tackling the Energy Limitations in Miniaturized Internet of Everything Devices
Abstract: Following Moore's law and Bell's law, miniaturization of electronic devices is continuously transforming the human life and the society. The next generation miniature devices are envisioned to ubiquitously connect physical objects in the world, digitizing cities, homes, industries, and human health and medicine. The major challenge in building these emerging hardware platforms is achieving all the desired sensing, computing, communication, and security functionalities under extreme power and size constraints. In this talk, I will present our recent efforts on unconventional circuit and systems designs to enable millimetric implantable bioelectronic medicine, and escalating security and intelligence of all sorts of edge devices. We take holistic design approaches to alleviate the energy issues without compromising system usability, exploring cross-disciplinary co-design opportunities from materials and devices, all the
way up to computing algorithms and programming languages. Specifically, I will present (1) magnetoelectric power and data transfer technologies to millimeter-sized battery-free bioelectronic implants, with system integrations and validations; (2) hardware-enabled foundational security primitives and modules fitting stringent power and cost budgets; and (3) processing in-memory systems for deep learning and stream processing with cross-layer designs.
Biography: Dr. Kaiyuan Yang is currently an Assistant Professor of ECE at Rice University, USA. He received his B.S. degree in Electronic Engineering from Tsinghua University, China, in 2012, and his Ph.D. degree in Electrical Engineering from the University of Michigan, Ann Arbor, MI, in 2017. His research interests include digital and mixed-signal circuit and system design for secure and intelligent microsystems, bioelectronics, and hardware security.
Dr. Yang is a recipient of the 2022 National Science Foundation (NSF) CAREER award, 2016 IEEE SSCS Predoctoral Achievement Award, and multiple best paper awards from premier conferences in various fields, including 2021 IEEE Custom Integrated Circuit Conference (CICC), 2016 IEEE Symposium on Security and Privacy (Oakland), 2015 IEEE International Symposium on Circuits
and Systems (ISCAS), and the Best Student Paper Award finalist at 2022 RFIC and 2019 CICC. He is currently serving as an associate editor of IEEE TVLSI and a co-chair of SSCS Houston chapter.
Host: Prof. Hashemi, Prof. Chen and Prof. Sideris
More Information: Abstract and Bio-Sept 16-Yang.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski