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Events for April 02, 2018

  • EE-EP Faculty Candidate, Marina Radulaski, Monday, April 2nd at 12pm in EEB 132

    Mon, Apr 02, 2018 @ 12:00 PM - 01:30 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Marina Radulaski, Stanford University

    Talk Title: Scalable Nanophotonics for Quantum and Classical Information Processing

    Abstract: Technological commodities of the 21st century come with exponential demands on information processing. While the electronic devices face physical limits of scalability, nanophotonics emerges as a leading solution for the Big Data manipulation. In the first part of the seminar, I will discuss the role of novel photonic architectures and robust device design algorithms in meeting the short-term classical hardware speedup goals. Moving toward the implementation of quantum information processing paradigms, I will evaluate applicability of color centers in silicon carbide and diamond to quantum computing, communication and cryptography. Finally, I will present advances in integration of color centers with nanoscale photonic devices serving as efficient quantum bits and quantum light sources.

    Biography: Marina Radulaski is a Nano- and Quantum Science and Engineering Postdoctoral Fellow at Stanford University's Ginzton Laboratory. She obtained a PhD in Applied Physics from Stanford University under the supervision of Prof. Jelena Vuckovic, a BSc/MSc in Physics from the University of Belgrade, Serbia, and a BSc/MSc in Computer Science from the Union University, Serbia. Marina was selected among the Rising Stars in EECS in 2017, Stanford Graduate Fellows 2012-2014, and Scientific American's "30-Under-30 Up and Coming Physicists" in 2012. She has performed research internationally at Berkeley Lab, Hewlett-Packard Labs, Oxford University, IQOQI Vienna, Helmholtz Center Berlin, and more. In addition to research, Marina enjoys building communities and promoting science through podcasts, videos and festivals.

    Host: EE-Electrophysics

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132

    Audiences: Everyone Is Invited

    Contact: Marilyn Poplawski

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  • Biomedical Engineering Seminars

    Mon, Apr 02, 2018 @ 12:30 PM - 01:50 PM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Kathy Nightingale, PhD, Professor, Duke University

    Talk Title: Ultrasonic Elasticity Imaging with Acoustic Radiation Force

    Abstract: Elasticity imaging involves introducing a mechanical tissue perturbation, imaging the resulting tissue response, and generating images that reflect the underlying mechanical properties of the tissue. Acoustic radiation force impulse (ARFI) based ultrasonic elasticity imaging methods have become widely available in the clinical market over the past five years. To date, these methods have found success clinically in the context of hepatic fibrosis staging and breast lesion characterization, with many additional applications under investigation. A major focus our laboratory has been the development and implementation of high resolution ARFI elasticity imaging methods for prostate cancer imaging and treatment guidance, with initial in vivo findings demonstrating that ARFI imaging is specific for clinically significant prostate cancer. Commercially available ARFI methods that evaluate shear wave propagation to provide quantitative stiffness estimates generally assume that the tissues are linear, isotropic, elastic, homogeneous, and incompressible in order to reconstruct the underlying material stiffness. Our recent work in shear wave imaging focuses on understanding the sources of error in these systems, and developing methods that address some of the underlying assumptions, i.e. using 3D volumetric imaging to analyze material anisotropy, using multi-dimensional filters and two and three dimensional shear wave monitoring to improve image quality in structured media, and exploring different approaches to estimate shearwave dispersion. In this talk, I will review the underlying physics and discuss the promise and limitations of these methods.

    Biography: Dr. Nightingale is the James L. and Elizabeth M. Vincent Professor of Biomedical Engineering at Duke University, and she is the director of the Duke Medical Imaging Training Program. Her research interests include ultrasonic and elasticity imaging and instrumentation. She has pioneered the development and clinical translation of acoustic radiation force based elasticity imaging techniques. She is the author of over 75 peer-reviewed journal articles in the areas of ultrasound and elasticity imaging, and has been awarded 9 patents. She has been a recipient of the Klein Family Distinguished Teaching Award, and the Marion Capers Distinguished Research and Teaching Award at Duke University. She has served on numerous NIH and DOD review panels and is currently a charter member of the BMIT-B NIH study section. She is an Associate Editor for Ultrasonic Imaging, a senior member of IEEE, and a fellow of the American Institute of Medical and Biological Engineering.

    Host: Professor Qifa Zhou

    Location: Olin Hall of Engineering (OHE) - 122

    Audiences: Everyone Is Invited

    Contact: Mischalgrace Diasanta

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  • Center for Systems and Control (CSC@USC) and Ming Hsieh Institute for Electrical Engineering

    Mon, Apr 02, 2018 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: TBA, TBA

    Talk Title: TBA

    Series: Joint CSC@USC/CommNetS-MHI Seminar Series

    Abstract: TBA

    Biography: TBA

    Host: Mihailo Jovanovic, mihailo@usc.edu

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132

    Audiences: Everyone Is Invited

    Contact: Gerrielyn Ramos

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  • EE Seminar - Robust Model-Free Control, Optimization, and Learning in Cyber-Physical Societal Systems

    Mon, Apr 02, 2018 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Jorge I. Poveda, University of California, Santa Barbara

    Talk Title: Robust Model-Free Control, Optimization, and Learning in Cyber-Physical Societal Systems

    Abstract: The deployment of advanced real-time control and optimization strategies in socially-integrated engineering systems could significantly improve our quality of life while creating jobs and economic opportunity. However, in cyber-physical systems such as smart grids, transportation networks, healthcare, and robotic systems, there still exist several challenges that prevent the implementation of intelligent control strategies. These challenges include the existence of limited communication networks, dynamic environments, multiple decision makers interacting with the system, and complex hybrid dynamics emerging from the feedback interconnection of physical processes and computational devices. In this talk, I will present a set of tools for the analysis and design of model-free feedback mechanisms that can cope with these challenges, and that are suitable for the real-time control and optimization of cyber-physical societal systems. The first part of the talk will focus on the problem of designing a class of robust model-free adaptive pricing mechanisms for systems such as the smart grids, transportation networks, and the Internet, where users behave in a selfish way, and where the objective of the social planner is to maximize the total welfare of the system. Next, I will show that this problem belongs to a broader family of model-free extremization problems, and I will present a general framework for the design of a family of algorithms that can successfully optimize the performance of cyber-physical systems having unknown mathematical models. Finally, I will illustrate how these results can be extended to achieve distributed control of large-scale autonomous systems by implementing novel robust coordination and synchronization feedback mechanisms. The talk will finish by discussing some future directions and preliminary results in the areas of data-driven hybrid control and security in stochastic learning dynamics.

    Biography: Jorge I. Poveda is a Ph.D. Candidate at the Center for Control, Dynamical Systems, and Computation (CCDC) at the University of California, Santa Barbara. He received the B.S. degrees in Electronics Engineering and Mechanical Engineering in 2012, and the M.S. degree (Magna Cum Laude) in Electrical Engineering in 2013, all from University of Los Andes, Bogota, Colombia, and the M.S. degree in Electrical and Computer Engineering from the University of California, Santa Barbara, USA, in 2015. He was a Research Intern with the Mitsubishi Electric Research Laboratories in Cambridge, MA, during the summers of 2016 and 2017. He received the 2013 CCDC Outstanding Scholar Fellowship at UCSB, and was a finalist for the Best Student Paper Award at the 56th IEEE Conference on Decision and Control in 2017. His main research interests lie at the intersection of robust feedback control theory, adaptive control, online optimization, and game theory, with applications to cyber-physical and societal systems.

    Host: Ashutosh Nayyar, ashutosn@usc.edu

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132

    Audiences: Everyone Is Invited

    Contact: Mayumi Thrasher

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