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Events for April 01, 2013
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Meet USC: Admission Presentation, Campus Tour, & Engineering TalkMon, Apr 01, 2013
Viterbi School of Engineering Undergraduate Admission
Receptions & Special Events
This half day program is designed for prospective freshmen and family members. Meet USC includes an information session on the University and the Admission process; a student led walking tour of campus and a meeting with us in the Viterbi School. Meet USC is designed to answer all of your questions about USC, the application process and financial aid. Reservations are required for Meet USC. This program occurs twice, once at 8:30 a.m. and again at 12:30 p.m. Please visit https://esdweb.esd.usc.edu/unresrsvp/MeetUSC.aspx to check availability and make an appointment. Be sure to list an Engineering major as your "intended major" on the webform!
Location: Ronald Tutor Campus Center (TCC) - USC Admission Office
Audiences: Everyone Is Invited
Contact: Viterbi Admission
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Convex Optimization for Systems Science: From Control to Statistics
Mon, Apr 01, 2013 @ 10:30 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Parikshit Shah, Ph.D., Wisconsin Institute of Discovery
Talk Title: Convex Optimization for Systems Science: From Control to Statistics
Abstract: Large-scale dynamic systems are becoming ubiquitous in modern science and engineering, with applications in diverse areas such as robotic teams, supply chains, and power networks. Systems science is an exciting area that deals with understanding systems and developing tools for analysis, model selection, and decision-making.
In this talk we will discuss two fundamental and challenging problems that arise in this area: (a) data-driven modeling of dynamic systems (traditionally known as system identification), and (b) decentralized decision making in the presence of limited information (also known as decentralized control). Some of the basic challenges in these problems are computational ones, which we will overcome by devising principled convex optimization based approaches. Along the way, we will establish novel connections between control and some combinatorial concepts such as partially ordered sets and Moebius inversion; and between system identification and high-dimensional statistics.
Biography: Parikshit Shah is currently a Member of Research Staff at Philips Research, New York. He has been a research associate at the University of Wisconsin (affiliated with the Wisconsin Institutes of Discovery) in 2011-2012. He received his PhD in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology in June 2011. Earlier, he received a Master's degree from Stanford and a Bachelor's degree from the Indian Institute of Technology, Bombay. His research interests lie in the areas of convex optimization, control theory, system identification, and statistics. He has held the School of Engineering Fellowship at Stanford University, and a visiting appointment at the Institute for Pure and Applied Mathematics (IPAM) at UCLA
Host: Prof. Richard Leahy
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Talyia Veal
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Seminars in Biomedical Engineering
Mon, Apr 01, 2013 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Mehmet Akcakaya, Ph.D., Instructor in Medicine, Harvard Medical School Senior Research Scientist, Cardiac MR Center, Beth Israel Deaconess Medical Center Harvard Medical School, Boston, MA
Talk Title: Acceleration Methods for High-Resolution Cardiac MRI Using Compressed Sensing
Host: Biomedical Engineering
Location: Olin Hall of Engineering (OHE) - 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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EE-EP Seminar
Mon, Apr 01, 2013 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Chris Mi, University of Michigan-Dearborn
Talk Title: Wireless Charging of Electric Vehicle Batteries for Economic and Safe Future Transportation
Abstract: Electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) have attracted worldwide attentions because of their capabilities to improve energy and environment sustainability. However, inconvenience of charging, high cost, short driving range, and safety concerns of the battery system have hindered the mass market penetration of EVs and PHEVs. This presentation will look at studies which address some of these issues.
The first part of the presentation will focus on wireless charging technology that helps eliminate the need of carrying cables and plugging in, and offer significant improvement in convenience and electric safety for EV and PHEV charging. Although Wireless Power Transmission (WPT) has been commercialized for consumer electronics and also investigated for EV wireless charging, the size, efficiency, and cost are key obstacles that prevent WPT from widely deployed. Our research in this area aims at novel designs that can considerably reduce size and cost while increase coupling coefficient and system efficiency. The second part will look at EV battery study that addresses safety and reliability concerns and provides diagnostic and prognostic functions. Finally, there will be some discussion on the latest research activities at the GATE Center of Electric Drive Transportation that further enhance safety and cost advantages of EVs and PHEVs.
Biography: Chris Mi is Professor of Electrical and Computer Engineering and the Director of DOE funded GATE Center for Electric Drive Transportation at the University of Michigan, Dearborn. He is a fellow of IEEE. He received the B.S. and M.S. degrees from Northwestern Polytechnical University, Xi’an, China, and the Ph.D. degree from the University of Toronto, Toronto, Canada, all in electrical engineering. Previously he was an Electrical Engineer with General Electric Canada Inc. He was the President and the Chief Technical Officer of 1Power Solutions, Inc. from 2008 to 2011.
His research interests are in electric and hybrid vehicles. He has taught tutorials and seminars on the subject of HEV/PHEV for the Society of Automotive Engineers (SAE), the IEEE, workshops sponsored by the National Science Foundation (NSF), and the National Society of Professional Engineers. He has delivered courses to major automotive OEMs and suppliers, including GM, Ford, Chrysler, Honda, Tyco Electronics, A&D Technology, Johnson Controls, Quantum Technology, Delphi, Siemens, and the European Ph.D School.
Dr. Mi is the recipient of “Distinguished Teaching Award” and “Distinguished Research Award” of University of Michigan Dearborn. He is the recipient of 2007 IEEE Region 4 “Outstanding Engineer Award,” IEEE Southeastern Michigan Section “Outstanding Professional Award.” and “SAE Environmental Excellence in Transportation (E2T) Award,” and ranked four times as “Top Associate Editors” by IEEE Transactions on Vehicular Technology. Dr. Mi is Associate Editor of three IEEE Transactions and an editorial board member of two IET Journals.
Dr. Mi was the Chair (2008-2009) and Vice Chair (2006-2007) of the IEEE Southeastern Michigan Section, the general Chair of the 5th IEEE Vehicle Power and Propulsion Conference. He is the topic chair for the 2011 IEEE International Future Energy Challenge, and the General Chair for the 2013 IEEE International Future Energy Challenge. He is a Distinguished Lecturer (DL) of the IEEE Vehicular Technology Society.
Host: EE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Harshvardhan Vathsangam, USC (PhD Defense)
Mon, Apr 01, 2013 @ 02:30 PM - 04:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Harshvardhan Vathsangam, USC
Talk Title: Sense and Sensibility: Statistical Techniques for Human Energy Expenditure Estimation Using Kinematic Sensors
Series: PhD Defense Announcements
Abstract: Sense and Sensibility: Statistical Techniques for Human Energy Expenditure Estimation Using Kinematic Sensors ==== Healthcare is undergoing a shift from the episodic, expert-driven, curative approaches of the past towards a self-empowered, preventative model for the future. Central to this is the treatment of chronic illnesses. This treatment will require the adoption of behavioral changes on one's lifestyle. In this thesis, we focus on the negative effects of one such chronic illness: physically inactivity.
Regular physical activity is associated with decreased mortality, lower risk of cardiovascular disease, diabetes mellitus, colon and breast cancer.
Despite this knowledge, physical activity levels are not adequate.
Central to the need to get people to be more active is the ability to accurately measure and characterize physical activity in a cost-effective yet ubiquitous manner. One dimension of characterization of physical activity is the energy expended as a result of that activity. In this dissertation, we aim to demonstrate how kinematic sensors in combination with statistical techniques can accurately predict energy expenditure due to physical activity.
We cast the problem of determining energy expenditure in a mathematical framework and discuss various functional maps. We derive a set of frequency-based features that are robust to location on the human body and orientation. We use these features to determine the most accurate 'per-person' technique to map movement to energy expenditure. We compare prediction accuracies using different sensor streams and algorithms. A comparative study of accuracy versus inference time is also performed. We extend this work to be able to generate maps given a minimal set of morphological descriptors such as height, weight, age etc. We present and compare a set of models including nearest neighbor models, weight-scaled models, a set of hierarchical linear models and speed-based approaches. We show how these approaches can be used to evaluate the best subset of morphological descriptors and the best individual descriptor to generate personalized maps across people. These contributions are a step towards designing cost-effective, accurate and ubiquitous solutions to estimate physical activity levels and designing interventions based on accurately measured data.
Host: Lizsl DeLeon
Location: Ronald Tutor Hall of Engineering (RTH) - 406
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
