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Events for the 5th week of September
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Discover USC: Bay Area - Santa Clara
Sun, Sep 24, 2017 @ 02:00 PM - 04:00 PM
Viterbi School of Engineering Undergraduate Admission
Receptions & Special Events
Join Viterbi Admission - along with the USC Admission & Financial Aid staff - at the Discover USC Program in Santa Clara.
Discover USC, a program for high school seniors, is a 2-hour info session that will cover: the USC Application Process, Financial Aid, Life on Campus, Plus, an Engineering Session led by Paul Ledesma, Director of Admission, USC Viterbi School of Engineering.
RSVP for Discover USCLocation: Hyatt Regency Santa Clara
Audiences: Prospective Freshmen & Family Members
Contact: Viterbi Admission
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Discover USC: South Florida
Sun, Sep 24, 2017 @ 02:00 PM - 04:00 PM
Viterbi School of Engineering Undergraduate Admission
Receptions & Special Events
Join the USC Admission Office at the Discover USC admission program in South Florida.
This program provides high school seniors and their families with an opportunity to meet admission counselors, alumni, and other prospective students and their parents.
RSVP for Discover USCLocation: The Diplomat Beach Resort Hollywood
Audiences: Prospective Freshmen & Family Members
Contact: Viterbi Admission
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Meet USC: Admission Presentation, Campus Tour, and Engineering Talk
Mon, Sep 25, 2017
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. During the engineering session we will discuss the curriculum, research opportunities, hands-on projects, entrepreneurial support programs, and other aspects of the engineering 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 make sure to check availability and register online for the session you wish to attend. Also, remember to list an Engineering major as your "intended major" on the webform!
RSVPLocation: Ronald Tutor Campus Center (TCC) - USC Admission Office
Audiences: Prospective Freshmen & Family Members
Contact: Viterbi Admission
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MHI Pioneer Series
Mon, Sep 25, 2017 @ 03:00 AM - 05:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Andrew Viterbi, University of Southern California Trustee, Presidential Chair, and Professor of Electrical Engineering
Talk Title: "It was the worst of times, it was the best of times." (with apologies to Mr. Dickens)
Series: MHI Pioneer Series
Abstract: The last two thirds of the 20th Century was a period of tremendous upheaval and progress, social, political and especially technological. This was the period during which I pursued two careers which were tightly intertwined. Curiously both were also influenced by our nation's most threatening competitor, Russia.
The first was my academic career and the second my entrepreneurial career, both of which covered over thirty years, with considerable overlap. Though unrecognized at the time, my academic research had roots in the work of the Russian mathematician Andrei Markov, while with full recognition, my entrepreneurial career was launched and initially supported by our Defense research efforts to counter the Soviet threat.
From 1957, when I arrived at Caltech's JPL just before the launch of Sputnik, until 2000 when I retired from Qualcomm, I was involved in furthering the knowledge, understanding and implementation of wireless digital communication, first for space and ultimately for cellular networks. My academic achievements, which have given me the most satisfaction, were primarily in the fields of synchronization and of error-suppressing coding. My entrepreneurial efforts were in support of the founding of two digital communication companies, Linkabit and Qualcomm, whose technologists achieved important breakthroughs through the practical realization of communication theory principles. Among these were the first Viterbi decoder now ubiquitous in digital wireless handsets, the first fully digitally implemented satellite modem, the first mobile satellite terrestrial network and the first spread spectrum digital cellular networks, which enabled the rise of a myriad of applications.
In the new millennium, to prevent boredom and counter aging, my time has been devoted partly to activities on corporate boards of startup companies in digital communication, data storage and their numerous applications. My Memoir, "Reflections of an Educator, Researcher and Entrepreneur," was published recently.
Host: Ming Hsieh Institute
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Cathy Huang
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Center for Systems and Control (CSC@USC) and Ming Hsieh Institute for Electrical Engineering
Mon, Sep 25, 2017 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Angelia Nedich, Arizona State University
Talk Title: Fast Distributed Algorithms for Optimization and Resource Sharing in Networks
Abstract: We will discuss the problems of distributed optimization over graphs. For the case of undirected graphs, we introduce a distributed algorithm, referred to as DIGing, which is a combination of a distributed inexact gradient method and a gradient-tracking mechanism. The DIGing algorithm uses doubly stochastic mixing matrices and employs fixed step-sizes and, yet, drives all agents' iterates to a common global minimizer. When the graphs are directed, in which case the implementation of doubly stochastic mixing matrices is unrealistic, we construct an algorithm that incorporates the push-sum protocol into the DIGing structure, thus obtaining Push-DIGing algorithm. Under the strong convexity assumption for the objective function, we prove that both algorithms converge at R-linear (geometric) rates, as long as the step-sizes do not exceed some upper bounds. We establish explicit convergence rate estimates for the convergence rates. When the graph is undirected, we show that the convergence rate of DIGing scales polynomially in the number of agents. We also provide some numerical experiments to demonstrate the efficacy of the proposed algorithms and to validate our theoretical findings. We then discuss the variants of these algorithms for resource allocation problems in graphs.
Biography: Angelia Nedich holds a Ph.D. from Moscow State University, Moscow, Russia, in Computational Mathematics and Mathematical Physics (1994), and a Ph.D. from Massachusetts Institute of Technology, Cambridge, USA in Electrical and Computer Science Engineering (2002). She has worked as a senior engineer in BAE Systems North America, Advanced Information Technology Division at Burlington, MA. She is the recipient of an NSF CAREER Award 2007 in Operations Research for her work in distributed multi-agent optimization. She is a recipient (jointly with her co-authors) of the Best Paper Award at the Winter Simulation Conference 2013 and the Best Paper Award at the International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt) 2015 (with co-authors). She has served as Associate Editor for IEEE Transactions on Automatic Control and Transactions of Control of Network Systems. She is currently serving on Editorial Board of SIAM Journal on Optimization and for INFORMS Operations Research. Her current interest is in large-scale optimization, games, control and information processing in networks.
Host: Mihailo Jovanovic, mihailo@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
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Seminars in Biomedical Engineering
Mon, Sep 25, 2017 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Nitin Mehta (alumnus, USC BME M.S. program), Cardiac Implant and Catheter Expert, TUV SUD America
Talk Title: Research Presentation & Career Path
Host: Stacey Finley, PhD
Location: Olin Hall of Engineering (OHE) - 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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Boeing Info Session
Mon, Sep 25, 2017 @ 06:00 PM - 08:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Boeing Information Session
Location: Seeley G. Mudd Building (SGM) - 101
Audiences: All Viterbi Students
Contact: RTH 218 Viterbi Career Connections
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Discover USC: Sacramento
Mon, Sep 25, 2017 @ 07:00 PM - 09:00 PM
Viterbi School of Engineering Undergraduate Admission
Receptions & Special Events
Join the USC Admission Office at the Discover USC admission program in Sacramento.
This program provides high school seniors and their families with an opportunity to meet admission counselors, alumni, and other prospective students and their parents.
RSVP for Discover USCLocation: Sheraton Grand Sacramento Hotel
Audiences: Prospective Freshmen & Family Members
Contact: Viterbi Admission
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VIRTUAL Workshop: Get Connected for Maximum Job Search Success
Tue, Sep 26, 2017 @ 02:00 PM - 03:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Find out how to build relationships & connections to assist you in your academic career & in your job search. Develop the 30 Second Commercial you need to interact with employers.
2 - 3 PM
To join the webinar, go to https://bluejeans.com/8071179753 and log in using your NetID and password.Location: ONLINE
Audiences: Everyone Is Invited
Contact: RTH 218 Viterbi Career Connections
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Center for Systems and Control (CSC@USC) and Ming Hsieh Institute for Electrical Engineering
Tue, Sep 26, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Evangelos Theodorou, Georgia Institute of Technology
Talk Title: The Science of Autonomy: a "Happy" Symbiosis Among Learning, Control, and Physics
Series: Fall 2017 Joint CSC@USC/CommNetS-MHI Seminar Series
Abstract: In this talk, I will present an information theoretic approach to stochastic optimal control that has advantages over classical methodologies and theories for decision making under uncertainty. The main idea is that there are certain connections between optimality principles in control and information theoretic inequalities in statistical physics that allow us to solve hard decision making problems in robotics, autonomous systems and beyond. There are essentially two different points of view of the same "thing" and these two different points of view overlap for a fairly general class of dynamical systems that undergo stochastic effects. The information theoretic approach can also be used in a game theoretic setting for teams of robots performing cooperative or non-cooperative tasks. I will also present a holistic view to autonomy that collapses planning, perception and control into one computational engine, and ask questions related to how organization and structure relates to functionality and performance in "engineered" organisms. The last part of my talk includes computational frameworks for uncertainty representation and suggests ways to incorporate these representations within decision making and control.
Biography: Evangelos A. Theodorou is an assistant professor with the Guggenheim School of aerospace engineering at Georgia Institute of Technology. He is also affiliated with the Institute of Robotics and Intelligent Machines. Evangelos Theodorou earned his Diploma in Electronic and Computer Engineering from the Technical University of Crete (TUC), Greece in 2001. He has also received a MSc in Production Engineering from TUC in 2003, a MSc in Computer Science and Engineering from University of Minnesota in spring of 2007 and a MSc in Electrical Engineering on dynamics and controls from the University of Southern California (USC) in Spring 2010. In May of 2011 he graduated with his PhD, in Computer Science at USC. After his PhD, he was a Postdoctoral Research Fellow with the department of computer science and engineering, University of Washington, Seattle. Evangelos Theodorou is the recipient of the King-Sun Fu best paper award of the IEEE Transactions on Robotics for the year 2012 and recipient of the best paper award in cognitive robotics in International Conference of Robotics and Automation 2011. He was also the finalist for the best paper award in International Conference of Humanoid Robotics in 2010 and International Conference of Robotics and Automation in 2017. His theoretical research spans the areas of stochastic optimal control theory, machine learning, information theory, and statistical physics. Applications involve learning, planning and control in autonomous, robotics and aerospace systems.
Host: Mihailo Jovanovic, mihailo@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
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Epstein Institute Seminar, ISE 651
Tue, Sep 26, 2017 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Nozer D. Singpurwalla, Emeritus Professor of Statistics and Distinguished Research Professor, George Washington University
Talk Title: The Dinegentropy of Diagnostic and Detection Tests
Host: Prof. Sheldon Ross
More Information: September 26, 2017.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - GER 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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CS Colloquium: Kai-Wei Chang (UCLA) - Structured Predictions: Practical Advancements and Applications in Natural Language Processing
Tue, Sep 26, 2017 @ 03:30 PM - 04:50 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Kai-Wei Chang, University of California, Los Angeles
Talk Title: Structured Predictions: Practical Advancements and Applications in Natural Language Processing
Abstract: This lecture satisfies requirements for CSCI 591: Research Colloquium.
Many machine learning problems involve making joint predictions over a set of mutually dependent output variables. The
dependencies between output variables can be represented by a structure, such as a sequence, a tree, a clustering of nodes, or a graph. Structured prediction models have been proposed for problems of this type, and they have been shown to be successful in many application areas, such as natural language processing, computer vision, and bioinformatics. In this talk, I will describe a collection of results that improve several aspects of these approaches. Our results lead to efficient learning algorithms for structured prediction models, which, in turn, support reduction in problem size, improvements in
training and evaluation speed. I will also discuss potential risks and challenges when using structured prediction models.
Related information is at https://urldefense.proofpoint.com/v2/url?u=http-3A__www.cs.virginia.edu_-7Ekc2wc_talk_sp.html&d=DwIBaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=LW6zU4yKxktEWcUPnmtKow&m=gw-3C-3UJqv9mPCsdDWaZHFxfXoQ6oXlSMsVWGL1xE0&s=l7eOcCL3YxMMSSFD4dVdUUMKTrGVB5Z8Dm0VD1cHVDM&e=
Biography: Kai-Wei Chang is an assistant professor in the Department of Computer Science at the University of California at Los Angeles. He has published broadly in machine learning and natural language processing. His research has mainly focused on designing machine learning methods for handling large and complex data. He has been involved in developing several machine learning libraries, including LIBLINEAR, Vowpal Wabbit, and Illinois-SL. He was an assistant professor at the University of Virginia in 2016-2017. He obtained his Ph.D. from the University of Illinois at Urbana-Champaign in 2015 and was a post-doctoral researcher at Microsoft Research in 2016. Kai-Wei was awarded the KDD Best Paper Award (2010), EMNLP Best Long Paper Award (2017), and the Yahoo! Key Scientific Challenges Award (2011).
Additional information is available at https://urldefense.proofpoint.com/v2/url?u=http-3A__kwchang.net&d=DwIBaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=LW6zU4yKxktEWcUPnmtKow&m=gw-3C-3UJqv9mPCsdDWaZHFxfXoQ6oXlSMsVWGL1xE0&s=wik3X8kutwqg-z2gIVP9M7W-uRkf04mPpX4HhWqxCDM&e=.
Host: Fei Sha
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Computer Science Department
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Clark Construction Info Session
Tue, Sep 26, 2017 @ 06:00 PM - 07:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Clark Construction Information Session
Location: Seeley G. Mudd Building (SGM) - 101
Audiences: All Viterbi Students
Contact: RTH 218 Viterbi Career Connections
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Crowdstrike Cyber Security Tech Talk
Tue, Sep 26, 2017 @ 06:30 PM - 08:00 PM
Viterbi School of Engineering Student Organizations
Workshops & Infosessions
CrowdStrike was founded in 2011 to fix a fundamental problem: The sophisticated attacks that were forcing the world's leading businesses into the headlines could not be solved with existing malware-based defenses. Co-founders George Kurtz and Dmitri Alperovitch realized that a brand new approach was needed -- one that combines the most advanced endpoint protection with expert intelligence to pinpoint the adversaries perpetrating the attacks, not just the malware.
CrowdStrike burst onto the national scene during the U.S. election season last year when it became the first to pin a data breach at the Democratic National Committee on Russia. They recently closed a $100 million funding round at a valuation exceeding $1 billion.
COME NETWORK WITH PROFESSIONALS FROM THE TEAM.
Follow us:
Like our FB Page: https://www.facebook.com/cyborgatusc/
Join our LinkedIn Group: https://www.linkedin.com/groups/10347148
Sign up for our mailing list: https://goo.gl/forms/UD9A7e2DPMbaZXkq1
Join our FB Group: https://www.facebook.com/groups/cyborgatusc/
Club Dues are strongly encouraged and can be paid while you sign in for each respective event.
Venmo Handle: @USC-Cyborg
$15/semester or $25/yearMore Information: CybOrg Event Flyer 2.jpg
Location: James H. Zumberge Hall Of Science (ZHS) - 252
Audiences: Everyone Is Invited
Contact: USC CybOrg
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Meet USC: Admission Presentation, Campus Tour, and Engineering Talk
Wed, Sep 27, 2017
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. During the engineering session we will discuss the curriculum, research opportunities, hands-on projects, entrepreneurial support programs, and other aspects of the engineering 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 make sure to check availability and register online for the session you wish to attend. Also, remember to list an Engineering major as your "intended major" on the webform!
RSVPLocation: Ronald Tutor Campus Center (TCC) - USC Admission Office
Audiences: Prospective Freshmen & Family Members
Contact: Viterbi Admission
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A Book Talk about A MIND AT PLAY: HOW CLAUDE SHANNON INVENTED THE INFORMATION AGE
Wed, Sep 27, 2017 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Jimmy Soni, Author
Talk Title: A Book Talk about A MIND AT PLAY: HOW CLAUDE SHANNON INVENTED THE INFORMATION AGE
Abstract: Claude Shannon was a groundbreaking polymath, a brilliant tinkerer, and a digital pioneer. He constructed a fleet of customized unicycles and a flamethrowing trumpet, outfoxed Vegas casinos, and built juggling robots. He also wrote the seminal text of the digital revolution, which has been called "the Magna Carta of the Information Age." His discoveries would lead contemporaries to compare him to Albert Einstein and Isaac Newton. His work anticipated by decades the world we'd be living in today - and gave mathematicians and engineers the tools to bring that world to pass.
In this elegantly written, exhaustively researched biography, Jimmy Soni and Rob Goodman reveal Claude Shannon's full story for the first time. It's the story of a small-town Michigan boy whose career stretched from the era of room-sized computers powered by gears and string to the age of Apple. It's the story of the origins of our digital world in the tunnels of MIT and the "idea factory" of Bell Labs, in the "scientists' war" with Nazi Germany, and in the work of Shannon's collaborators and rivals, thinkers like Alan Turing, John von Neumann, Vannevar Bush, and Norbert Wiener.
And it's the story of Shannon's life as an often reclusive, always playful genius. With access to Shannon's family and friends, A Mind at Play brings this singular innovator and creative genius to life.
Biography: Jimmy Soni was managing editor at The Huffington Post from January 2012-2014. Previously he had worked as a strategy consultant at McKinsey and Company, as well as a speech writer at the office of the Mayor of the District of Columbia. Soni has co-authored several pieces with fellow Duke graduate Rob Goodman; their work has been featured in Politico, The Huffington Post, Business Insider, AdWeek, and The Atlantic, among others.
In 2012, Jimmy, published his first book a biography of Cato the Younger, titled Rome's Last Citizen: The Life and Legacy of Cato, Mortal Enemy of Caesar.
Host: Center for Cyber-Physical Systems and the Internet of Things
More Information: CCI_Shannon_BookTalk_September27_2017.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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CCI Seminar: Jimmy Soni – A Mind at Play: How Claude Shannon Invented the Information Age
Wed, Sep 27, 2017 @ 10:00 AM - 11:00 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Jimmy Soni,
Talk Title: A Mind at Play: How Claude Shannon Invented the Information Age
Abstract: Claude Shannon was a groundbreaking polymath, a brilliant tinkerer, and a digital pioneer. He constructed a fleet of customized unicycles and a flamethrowing trumpet, outfoxed Vegas casinos, and built juggling robots. He also wrote the seminal text of the digital revolution, which has been called "the Magna Carta of the Information Age." His discoveries would lead contemporaries to compare him to Albert Einstein and Isaac Newton. His work anticipated by decades the world we'd be living in today-”and gave mathematicians and engineers the tools to bring that world to pass.
In this elegantly written, exhaustively researched biography, Jimmy Soni and Rob Goodman reveal Claude Shannon's full story for the first time. It's the story of a small-town Michigan boy whose career stretched from the era of room-sized computers powered by gears and string to the age of Apple. It's the story of the origins of our digital world in the tunnels of MIT and the "idea factory" of Bell Labs, in the "scientists' war" with Nazi Germany, and in the work of Shannon's collaborators and rivals, thinkers like Alan Turing, John von Neumann, Vannevar Bush, and Norbert Wiener.
And it's the story of Shannon's life as an often reclusive, always playful genius. With access to Shannon's family and friends, A Mind at Play brings this singular innovator and creative genius to life.
Biography: Jimmy Soni was managing editor at The Huffington Post from January 2012-2014. Previously he had worked as a strategy consultant at McKinsey and Company, as well as a speech writer at the office of the Mayor of the District of Columbia. Soni has co-authored several pieces with fellow Duke graduate Rob Goodman; their work has been featured in Politico, The Huffington Post, Business Insider, AdWeek, and The Atlantic, among others.
In 2012, Jimmy, published his first book a biography of Cato the Younger, titled Rome's Last Citizen: The Life and Legacy of Cato, Mortal Enemy of Caesar.
Host: Center for Cyber-Physical Systems and the Internet of Things
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Computer Science Department
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Amgen Seminar: Bryan Moyer
Wed, Sep 27, 2017 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Bryan Moyer, Amgen
Talk Title: Nav1.7 drug development for pain
Series: USC/Amgen Seminar Series
Host: USC/Amgen
More Info: http://stemcell.usc.edu/events
Audiences: Everyone Is Invited
Contact: Cristy Lytal/USC Stem Cell
Event Link: http://stemcell.usc.edu/events
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Computer Science General Faculty Meeting
Wed, Sep 27, 2017 @ 12:00 PM - 02:00 PM
Thomas Lord Department of Computer Science
Receptions & Special Events
Bi-Weekly regular faculty meeting for invited full-time Computer Science faculty only. Event details emailed directly to attendees.
Location: Ronald Tutor Hall of Engineering (RTH) - 526
Audiences: Invited Faculty Only
Contact: Assistant to CS chair
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute for Electrical Engineering Joint Seminar Series on Cyber-Physical Systems
Wed, Sep 27, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Eric Feron , Professor, Georgia Institute of Technology
Talk Title: 20 Years of Aerobatic Flight with Autonomous Air Vehicles
Abstract: The past 20 years have seen a remarkable evolution of the drone technology. Back in 1997, academia had to deal with heavy, bulky and expensive machines powered by cranky internal combustion engines. Unmanned vehicles today are a lot cheaper, lighter, and reliable, making them a lot more approachable by students and faculty alike. After tracing our research back to the late 1990s, this talk will introduce an aerobatic drone capable of producing reduced- or zero-gravity conditions at an affordable cost. The platform is still a prototype, but it captures most of the difficulties faced by the larger platform of our dreams. The controller design will be discussed, and a full non-linear maneuver stability analysis will be presented that mixes the concept of transverse dynamics with well-known concepts from robust control. This is joint work with John Hauser (U. Colorado, Boulder) and Pablo Afman (Georgia Tech).
Biography: Eric Feron is a professor at Georgia Tech, where he directs the Decision and Control Laboratory. His basic training is in applied mathematics, computer science, and operations research. His interests include aerospace systems and robotics. Noteworthy achievements include an airport congestion control algorithm now used at many major airports (1999), the first aerobatic autonomous air vehicle (2001), the english translation of Ãtienne Bézout's General Theory of Algebraic Equations (2006), and a course on cyber-physical systems offered by Georgia Tech as part of its Online Master of Science in Computer Science (2017).
Host: Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Estela Lopez
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Aerospace & Mechanical Engineering Seminar
Wed, Sep 27, 2017 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: James Friend, Professor/UCSD
Talk Title: Acoustic Nanofluidics
Abstract: Acoustic waves have found new utility in microfluidics, providing an enormously powerful ability to manipulate fluids and suspended particles in open and closed fluid systems. In this talk, we cover some fundamental and powerful concepts of acoustic wave generation and propagation often overlooked in the literature, and follow it with exploration of new phenomena observed at the nanoscale. In fact, the usefulness of acoustic waves at the micro-scale is even more compelling at the nano-scale, in ways not predicted by classical theory. Particle deagglomeration, fluid pumping, pattern formation, and other curious physical phenomena will be shown in the context of potentially useful applications. Along the way, the fascinating underlying physics tying together the acoustics, fluid dynamics, and free fluid interface in these systems will be described.
Biography: James Friend James Friend is a Professor in the Center for Medical Devices and Instrumentation, Department of Mechanical and Aerospace Engineering, at the University of California, San Diego, having received his PhD in mechanical engineering from the University of Missouri-Rolla in 1998. His research interests are diverse, but principally lie in exploring and exploiting acoustic and vibration phenomena at small scales. He has over 260 peer-reviewed research publications, including 138 journal papers and eight book chapters, and 27 patents in process or granted, completed 33 postgraduate students and supervised 18 postdoctoral staff, and been awarded over $25 million in competitive grant-based research funding over his career. He has been fortunate to receive an AIAA Jefferson Goblet Student Paper Award and an ASME Best Paper of Conference Award for a single talk at the AIAA/ASME/AHS/ASC/ASCE Structural Dynamics & Mechanics Conference in 1996; excellence in teaching, early career research, and research awards from the Monash Faculty of Engineering in 2006, 2008, and 2011, respectively; a Future Leader award from the Davos Future Summit in 2008; a Top 10 emerging scientific leader of Australia by Microsoft and The Australian newspaper award in 2009; an award as the corresponding author of one of the top 50 papers of the past 50 years of Applied Physics Letters in 2012; and the IEEE Carl Hellmuth Hertz Ultrasonics Award from the IEEE in 2015.
Host: Department of Aerospace and Mechanical Engineering
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Ashleen Knutsen
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USC LACI’s Life of a Consultant
Thu, Sep 28, 2017 @ 11:00 AM - 12:00 PM
Viterbi School of Engineering Student Organizations
University Calendar
Interested in exploring a career in consulting? Come to Los Angeles Community Impact's Life of a Consultant event on Thursday, September 28th from 7:30-9:30pm! Meet consultants from several industry-leading firms in a small group setting as they answer your questions about a consultant's typical work day, the recruiting process, the unique culture at each firm, and more. Light refreshments will be served.
You can RSVP for the event here: http://bit.ly/2xLWcrg. The link will go live on Wednesday, September 13 at 9:00AM, and you have to submit a $10 refundable deposit in order to confirm your place at the event. Contact LACI External Relations at laci.ambassador@gmail.com for any questions.Location: USC University Club, 705 W 34th St, Los Angeles, CA 90089
Audiences: Undergrad
Contact: usclatch
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The biomedical literature captures the most current biomedical knowledge and is a tremendously rich resource for research with over 26 million publications currently indexed in the US National Library of Medicine’s PubMed repository. Large-scale processin
Thu, Sep 28, 2017 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Karin Verspoor, University of Melbourne
Talk Title: The scientific literature as a resource for biological prediction and data validation
Abstract: The biomedical literature captures the most current biomedical knowledge and is a tremendously rich resource for research with over 26 million publications currently indexed in the US National Library of Medicines PubMed repository. Large scale processing of the literature enables direct biomedical knowledge discovery. In this presentation, I will introduce the use of text mining techniques for applications in protein function and phenotype prediction. I will also explore a novel alternative use of the literature to support curation of biological database records by cross checking their content with associated literature this work further broadens the value of the literature in bioinformatics applications.
Biography: Karin is a Professor in the School of Computing and Information Systems and Deputy Director of the Health and Biomedical Informatics Centre at the University of Melbourne. Her research focuses on text analytics and machine learning for biomedical applications, to enable knowledge extraction from unstructured data as well as to provide clinical decision support. A current active project is related to enabling precision medicine with machine learning.
Karin was previously the Scientific Director for Health and Life Sciences at NICTA. Prior to arriving in Australia from the United States she held research roles at the University of Colorado School of Medicine and Los Alamos National Laboratory, and spent 5 years developing language technology software in two start up companies.
Host: Gully Burns
Location: Information Science Institute (ISI) - 11th floor large conference room
Audiences: Everyone Is Invited
Contact: Kary LAU
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Scaling Machine Learning Performance with Moore's Law
Thu, Sep 28, 2017 @ 02:00 PM - 03:15 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Kunle Olukotun, Stanford University
Talk Title: Scaling Machine Learning Performance with Moore's Law
Abstract: The computational demands of machine learning (ML) requires energy efficient machine learning specific accelerators. This naturally results in heterogeneous computing platforms composed of CPUs and ML Accelerators. However, the staggering cost (the majority of the cost is for software development) of designing custom integrated circuits for many application domains makes it cost-prohibitive to design these accelerators. This situation calls for a new paradigm for designing accelerators that can provide energy-efficient ML-specific performance and easier software development. The key to this new paradigm is to enable application developers to optimize the underlying hardware to make it specific to their ML application needs. The new design paradigm consists of new application ML-specific programing languages, new machine learning algorithms, new compilation technology to target both existing (FPGAs) and new (Software Defined Hardware) reconfigurable architectures.
Biography: Kunle Olukotun is the Cadence Design Systems Professor of Electrical Engineering and Computer Science at Stanford University. Olukotun is well known as a pioneer in multicore processor design and the leader of the Stanford Hydra chip multipocessor (CMP) research project. Olukotun founded Afara Websystems to develop high-throughput, low-power multicore processors for server systems. The Afara multicore processor, called Niagara, was acquired by Sun Microsystems. Niagara derived processors now power all Oracle SPARC-based servers. Olukotun currently directs the Stanford Pervasive Parallelism Lab (PPL), which seeks to proliferate the use of heterogeneous parallelism in all application areas using Domain Specific Languages (DSLs). Olukotun is a member of the Data Analytics for What's Next (DAWN) Lab which is developing infrastructure for usable machine learning. Olukotun is an ACM Fellow and IEEE Fellow for contributions to multiprocessors on a chip and multi-threaded processor design. Olukotun received his Ph.D. in Computer Engineering from The University of Michigan.
Host: Xuehai Qian, x04459, xuehai.qian@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
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CS Colloquium Event: Facebook Tech Talk
Thu, Sep 28, 2017 @ 03:30 PM - 04:50 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Alex Helm, Catrina Manahan, Charles Kuykendoll, Yuandong Tian, Min Li, Qiachao Que, See Biography
Talk Title: AI in Games: Achievements and Challenges
Abstract: This lecture satisfies requirements for CSCI 591: Research Colloquium.
Recently, substantial progress of AI has been made in applications that require advanced pattern reading, including computer vision, speech recognition and natural language processing. However, it remains an open problem whether AI will make the same level of progress in tasks that require sophisticated reasoning, planning and decision making in complicated game environments similar to the real-world. In this talk, I present the state-of-the-art approaches to build such an AI, our recent contributions in terms of designing more effective algorithms and building extensive and fast general environments, as well as issues and challenges.
Biography: Yuandong Tian is a Research Scientist in Facebook AI Research, working on reasoning with deep learning in games and theoretical analysis of deep non-convex models. He is the leader researcher and engineer for DarkForest (Facebook Computer Go project). Prior to that, he was a Software Engineer/Researcher in Google Self-Driving Car team during 2013-2014. He received Ph.D. in Robotics Institute, Carnegie Mellon University on 2013, Bachelor and Master degree of Computer Science in Shanghai Jiao Tong University. He is the recipient of 2013 ICCV Marr Prize Honorable Mentions for his work on global optimal solution to non-convex optimization in image alignment.
Host: CS Department
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Ryan Rozan
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CAIS Seminar: Dr. Peng Shi (University of Southern California) - Prediction and Optimization in School Choice
Thu, Sep 28, 2017 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Peng Shi, University of Southern California
Talk Title: Prediction and Optimization in School Choice
Abstract: In public school choice, students submit preference rankings for a given set of schools to the school board, which takes into account everyone's choices to compute the assignment. An important policy lever is what choice options to offer to each neighborhood, and how to prioritize between students. A key trade-off is between giving students equitable chances to go to the schools they want and controlling the city's school busing costs.
We study the optimization problem of choosing the choice menus and priorities for each neighborhood in order to maximize the sum of utilitarian and max-min welfare, subject to capacity and transportation constraints. The optimization is built on top of a predictive model of how students will choose given new choice menus, which we validate using both out-of-sample testing and a field experiment. Under a large market approximation, the optimization reduces to an assortment planning problem in which the objective is social-welfare rather than revenue. We show how to efficiently solve this sub-problem under various discrete choice models, and use this to produce better menus and priorities for Boston, which we evaluate by discrete simulations.
Biography: Dr. Peng Shi is an Assistant Professor of Data Science and Operations at the USC Marshall School of Business. He is interested in developing quantitative methodologies for the betterment of society. His current research focuses on optimization in matching markets, with applications in school choice, public housing, and online marketplaces. His research on school choice won multiple awards, including the ACM SIGecom Doctoral Dissertation Award, the INFORMS Public Sector Operations Best Paper Competition, and the INFORMS Doing Good with Good OR Student Paper Competition. Prior to joining USC, he completed a PhD in Operations Research at MIT, and was a postdoctoral researcher at Microsoft Research.
Host: Milind Tambe
Location: Seeley Wintersmith Mudd Memorial Hall (of Philosophy) (MHP) - 101
Audiences: Everyone Is Invited
Contact: Computer Science Department
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Chevron IT Information Session
Thu, Sep 28, 2017 @ 05:30 PM - 07:30 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Location: Seeley G. Mudd Building (SGM) - 101
Audiences: All Viterbi Students
Contact: RTH 218 Viterbi Career Connections
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Meet USC: Admission Presentation, Campus Tour, and Engineering Talk
Fri, Sep 29, 2017
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. During the engineering session we will discuss the curriculum, research opportunities, hands-on projects, entrepreneurial support programs, and other aspects of the engineering 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 make sure to check availability and register online for the session you wish to attend. Also, remember to list an Engineering major as your "intended major" on the webform!
RSVPLocation: Ronald Tutor Campus Center (TCC) - USC Admission Office
Audiences: Prospective Freshmen & Family Members
Contact: Viterbi Admission
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Ming Hsieh Institute Seminar Series on Integrated Systems
Fri, Sep 29, 2017 @ 10:00 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Bodhisatwa Sadhu, Research Staff Member, IBM T.J. Watson Research Center
Talk Title: mmWave Radio Design for 5G Base-stations and Mobile Handsets
Host: Profs. Hossein Hashemi, Mike Chen, Mahta Moghaddam, and Dina El-Damak
More Information: MHI Seminar Series IS -Bodhisatwa Sadhu.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Jenny Lin
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AI Seminar
Fri, Sep 29, 2017 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Stefano Ermon, Stanford University
Talk Title: Learning with limited supervision
Abstract: Many of the recent successes of machine learning have been characterized by the availability of large quantities of labeled data. Nonetheless, we observe that humans are often able to learn with very few labeled examples or with only high level instructions for how a task should be performed. In this talk, I will present some new approaches for learning useful models in contexts where labeled training data is scarce or not available at all. I will first discuss and formally prove some limitations of existing training criteria used for learning hierarchical generative models. I will then introduce novel architectures and methods to overcome these limitations, allowing us to learn a hierarchy of interpretable features from unlabeled data. Finally, I will discuss ways to use prior knowledge (such as physics laws or simulators) to provide weak forms of supervision, showing how we can learn to solve useful tasks, including object tracking, without any labeled data.
Biography: Stefano Ermon is currently an Assistant Professor in the Department of Computer Science at Stanford University, where he is affiliated with the Artificial Intelligence Laboratory. He completed his PhD in computer science at Cornell in 2015. His research interests include techniques for scalable and accurate inference in graphical models, large-scale combinatorial optimization, and robust decision making under uncertainty, and is motivated by a range of applications, in particular ones in the emerging field of computational sustainability. Stefano's research has won several awards, including three Best Paper Awards, a World Bank Big Data Innovation Challenge, and was selected by Scientific American as one of the 10 World Changing Ideas in 2016. He is a recipient of the Sony Faculty Innovation Award and NSF CAREER Award.
Host: Aram Galstyan
Location: Information Science Institute (ISI) - 11th floor large conference room
Audiences: Everyone Is Invited
Contact: Kary LAU
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W.V.T. RUSCH ENGINEERING HONORS COLLOQUIUM
Fri, Sep 29, 2017 @ 01:00 PM - 02:00 PM
USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. Albert Dato, Department of Engineering, Harvey Mudd College
Talk Title: Fascinating Applications of Graphene
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Su Stevens
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PhD Defense - Matthias Hernandez
Fri, Sep 29, 2017 @ 01:00 PM - 02:30 PM
Thomas Lord Department of Computer Science
University Calendar
Committee:
Gerard Medioni (CS- chair)
Aiichiro Nakano (CS)
Antonio Ortega (EE)
PhD Candidate: Matthias Hernandez
Venue:
PHE 223 - Friday, September 29th 1PM-2:30PM
Title:
3D inference and registration with application to retinal image analysis and face analysis
Abstract:
Image registration is a fundamental topic in image analysis, with applications in tracking, biometrics, medical imaging or 3D reconstruction. It consists in aligning 2 or multiple images of the same scene that are taken in different conditions, such as from different viewpoints, from different sensors or at different times. Similarly, 2D/3D registration aims at aligning captured 2D images with a 3D model.
In this talk, we study registration problems in challenging cases in which traditional methods do not provide satisfactory results. We show that even weak prior knowledge on the 3D structure provides reliable information that can be used for accurate registration. Specifically, we focus on two specific cases: 2D/3D multimodal retinal imaging and 3D face reconstruction from low-resolution videos.
For retinal image registration, we propose an integrated framework for registering an arbitrary number of images of different modalities, including a 3D volume. We propose a generic method to extract salient line structures in many image modality, based on dense tensor voting, and a robust registration framework for multiple images. Our approach can handle large variations across modalities and is evaluated on real-world retinal images with 5 modalities per eye.
For 3D face modeling, we propose to constrain traditional Structure from Motion (SfM) with a face shape prior to guide the correspondence finding process. We initialize a 3D face model xon coarse facial landmarks. We perform 3D reconstruction by maximizing photometric consistency across the video over 3D shape, camera poses and facial expressions. We compare our method to several state-of-the-art methods and show that our method can generate more accurate reconstructions.
To assess the discriminability of the reconstructed models, we develop an end-to-end 3D-3D facial recognition algorithm. We leverage existing deep learning networks trained on 2D images and fine tune-them on images generated by orthogonal projection of 3D data. We show that while having low amounts of 3D data, our method provides excellent recognition results while being significantly more scalable than state-of-the-art methods.
Finally, while excellent recognition results can be achieved with laser-scan 3D data, we have observed that reconstructed facial 3D models cannot be relied on for recognition purposes. We analyze which level of accuracy is required for enabling reliable 3D face recognition, and which factors impact recognition from reconstructed data.
Location: Charles Lee Powell Hall (PHE) - 223
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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Munushian Seminar - Ming C. Wu, Friday, September 22nd at 2:00pm in EEB 132
Fri, Sep 29, 2017 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Ming C. Wu, University of California, Berkeley
Talk Title: Silicon Photonic MEMS
Abstract: Ming C. Wu is Nortel Distinguished Professor of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He is also Co-Director of Berkeley Sensor and Actuator Center (BSAC) and Faculty Director of UC Berkeley Marvell Nanolab. Dr. Wu received his M.S. and Ph.D. in Electrical Engineering and Computer Sciences from the University of California, Berkeley in 1988. He has been with AT&T Bell Laboratories, Murray Hill (1988-1992) and UCLA (1993 to 2004) before joining the faculty at Berkeley. His research interests include optoelectronics, nanophotonics, MEMS, and optofluidics. He has published 8 book chapters, over 500 papers in journals and conferences, and 25 issued U.S. patents.
Prof. Wu is an IEEE Fellow, and a Packard Foundation Fellow (1992 - 1997). He received the 2007 Paul F. Forman Engineering Excellence Award, the 2017 C.E.K. Mees Medal from Optical Society of America, and the 2016 William Streifer Award from IEEE Photonics Society.
Biography: Ming C. Wu is Nortel Distinguished Professor of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He is also Co-Director of Berkeley Sensor and Actuator Center (BSAC) and Faculty Director of UC Berkeley Marvell Nanolab. Dr. Wu received his M.S. and Ph.D. in Electrical Engineering and Computer Sciences from the University of California, Berkeley in 1988. He has been with AT&T Bell Laboratories, Murray Hill (1988-1992) and UCLA (1993 to 2004) before joining the faculty at Berkeley. His research interests include optoelectronics, nanophotonics, MEMS, and optofluidics. He has published 8 book chapters, over 500 papers in journals and conferences, and 25 issued U.S. patents.
Prof. Wu is an IEEE Fellow, and a Packard Foundation Fellow (1992 - 1997). He received the 2007 Paul F. Forman Engineering Excellence Award, the 2017 C.E.K. Mees Medal from Optical Society of America, and the 2016 William Streifer Award from IEEE Photonics Society.
Host: EE-Electrophysics
More Info: minghsiehee.usc.edu/about/lectures
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: minghsiehee.usc.edu/about/lectures
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Powering the Future of Imaging and Signal Processing with Data-Driven Systems
Fri, Sep 29, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Saiprasad Ravishankar, Electrical Engineering & Computer Science Department, University of Michigan
Talk Title: Powering the Future of Imaging and Signal Processing with Data-Driven Systems
Series: Medical Imaging Seminar Series
Abstract: The data-driven learning of signal models including dictionaries, sparsifying transforms, low-rank models, tensor and manifold models, etc., is of great interest in many applications. In this talk, I will present my research that developed efficient, scalable, and effective data-driven models and methodologies for signal processing and imaging. I will mainly discuss my work on transform learning. Various interesting structures for sparsifying transforms such as well-conditioning, double sparsity, union-of-transforms, incoherence, rotation invariance, etc., can be considered, which enable their efficient and effective learning and usage. Transform learning-driven approaches achieve promising results in applications such as image and video denoising, and X-ray computed tomography or magnetic resonance image (MRI) reconstruction from limited or corrupted data. The convergence properties of the algorithms will be discussed. I will also present recent work on efficient dictionary learning in combination with low-rank models, and demonstrate the usefulness of the resulting LASSI method for dynamic MRI. The efficiency and effectiveness of the methods proposed in my research may benefit a wide range of additional applications in imaging, computer vision, neuroscience, and other areas requiring data-driven parsimonious models. Finally, I will provide a brief overview of recent works on physics-driven deep training of image reconstruction algorithms, light field reconstruction from focal stacks, online data-driven estimation of dynamic data from streaming, limited measurements, etc.
Biography: Saiprasad Ravishankar received the B.Tech. degree in Electrical Engineering from the Indian Institute of Technology Madras, in 2008. He received the M.S. and Ph.D. degrees in Electrical and Computer Engineering, in 2010 and 2014 respectively, from the University of Illinois at Urbana-Champaign, where he was an Adjunct Lecturer in the Department of Electrical and Computer Engineering during Spring 2015, and a Postdoctoral Research Associate at the Coordinated Science Laboratory until August, 2015. Since then, he has been a Research Fellow in the Electrical Engineering and Computer Science Department at the University of Michigan. His research interests include signal, image and video processing, signal modeling, data science, dictionary learning, biomedical and computational imaging, data-driven methods, inverse problems, compressed sensing, machine learning, and large-scale data processing.He has received multiple awards including the Sri Ramasarma V Kolluri Memorial Prize from IIT Madras and the IEEE Signal Processing Society Young Author Best Paper Award for his paper Learning Sparsifying Transforms published in IEEE Transactions on Signal Processing.
Host: Professor Richard Leahy
Location: Ronald Tutor Hall of Engineering (RTH) - 105
Audiences: Everyone Is Invited
Contact: Talyia White
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute for Electrical Engineering Joint Seminar Series on Cyber-Physical Systems
Fri, Sep 29, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Yanzhi Wang , Syracuse University
Talk Title: Towards the limits of energy efficiency and performance of deep learning systems
Abstract: Deep learning systems have achieved unprecedented progresses in a number of fields such as computer vision, robotics, game playing, unmanned driving and aerial systems, and other AI-related fields. However, the rapidly expanding model size is posing a significant restriction on both the computation and weight storage, for both inference and training, and on both high-performance computing systems and low-power embedded system and IoT applications. In order to overcome these limitations, we propose a holistic framework of incorporating structured matrices into deep learning systems, and could achieve (i) simultaneous reduction on weight storage and computational complexities, (ii) simultaneous speedup of training and inference, and (iii) generality and fundamentality that can be adopted to both software and hardware implementations, different platforms, and different neural network types, sizes, and scalability.
Besides algorithm-level achievements, our framework has (i) a solid theoretical foundation to prove that our approach will converge to the same "effectiveness" as deep learning without compression, and to demonstrate/prove that our approach approach/achieve the theoretical limitation of computation and storage of deep learning systems; (ii) platform-specific implementations and optimizations on smartphones, FPGAs, and ASIC circuits. We demonstrate that our smartphone-based implementation achieves the similar speed of GPU and existing ASIC implementations on the same application. Our FPGA-based implementations for deep learning systems and LSTM networks could achieve 11X+ energy efficiency improvement compared with the best state-of-the-arts, and even higher energy efficiency gain compared with IBM TrueNorth neurosynaptic processor. Our proposed framework can achieve 3.5 TOPS computation performance in FPGAs, and is the first to enable nano-second level recognition speed for image recognition tasks.
Biography: Yanzhi Wang is currently an assistant professor in the Department of Electrical Engineering and Computer Science at Syracuse University, from August 2015. He has received his Ph.D. Degree in Computer Engineering from University of Southern California (USC) in 2014, under supervision of Prof. Massoud Pedram, and his B.S. Degree in Electronic Engineering from Tsinghua University in 2009.
Dr. Wang's current research interests are the energy-efficient and high-performance implementations of deep learning and artificial intelligence systems, neuromorphic computing and new computing paradigms, and emerging deep learning algorithms/systems such as Bayesian neural networks, generative adversarial networks (GANs), and deep reinforcement learning. Besides, he works on the application of deep learning and machine intelligence in various mobile and IoT systems, medical systems, and UAVs, as well as the integration of security protection in deep learning systems. He also works on near-threshold computing for IoT devices and energy-efficient cyber-physical systems. His group works on both algorithms and actual implementations (FPGAs, circuit tapeouts, mobile and embedded systems, and UAVs).
His work has been published in top venues in conferences and journals (e.g. ASPLOS, MICRO, ICML, DAC, ICCAD, DATE, ASP-DAC, ISLPED, INFOCOM, ICDCS, TComputer, TCAD, etc.), and has been cited for around 3,000 times according to Google Scholar. He has received four Best Paper or Top Paper Awards from major conferences including IEEE ICASSP (top 3 among all 2,000+ submissions), ISLPED, IEEE CLOUD, and ISVLSI. He has another six Best Paper Nominations and two Popular Papers in IEEE TCAD. His group is sponsored by the NSF, DARPA, IARPA, AFRL/AFOSR, Syracuse CASE Center, and industry sources.
Host: Paul Bogdan
Location: Corwin D. Denney Research Center (DRB) - 146
Audiences: Everyone Is Invited
Contact: Estela Lopez
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PhD Defense - Anh Tran
Fri, Sep 29, 2017 @ 02:30 PM - 04:00 PM
Thomas Lord Department of Computer Science
University Calendar
* PhD Candidate: Anh Tran
* Committee:
Gerard Medioni (chair)
Ram Nevatia
Sandeep Gupta (outside)
* Title: Face Recognition and 3D Face Modeling from images in the wild.
(I assume that I can change my thesis title from the one registered for the hooding ceremony)
* Time: Sep 29 (Fri) 2:30-4:00pm
* Room: PHE 223
* Abstract:
Face recognition and 3D face modeling are key problems in computer vision with many applications in biometrics, human-computer interactions, surveillance, entertainment, and many more. While we have witnessed improvements over the last few years, open problems remain when images and videos in the wild are considered. In this dissertation, we discuss how to address these problems effectively, as well as the connection between them. Face recognition must address appearance changes due to 3D factors, such as head pose, face shape, and expression. Second, 3D face modeling recovers stable and recognizable 3D shape.
The first part of this thesis focuses on face recognition in the wild. We show that by coupling 3D face augmentation with a state-of-the-art 2D face recognition engine, we can greatly boost recognition accuracy. Our 3D face augmentation synthesizes facial images with different 3D head poses, 3D shapes, and expressions, thereby making our system robust to facial variations introduced by these factors. Our end-to-end system shows state-of-the-art performances on the latest challenging face recognition benchmarks. We also present some additional novel techniques to enhance the proposed system, from speeding-up rendering and matching to a complete landmark-free pipeline, which makes our system scalable and robust to a very-large training data and further break in-the-wild recognition records.
Inferring the accurate 3D geometry of a face from one or more images is a challenging problem. In the second part of this thesis, we present robust methods to build 3D morphable face models (3DMM), and validate the quality with face recognition tests. First, we define the state of the art of traditional analysis-by-synthesis 3DMM methods. Particularly, we investigate the impact of multiple inputs on the 3D modeling results in both accuracy and distinctiveness. From this observation, we then generate a large amount of 3D "ground-truth" faces, and train a convolutional neural network (CNN) to regress 3D shape and texture directly from any single input photo. The 3D estimates produced by our CNN surpass the state-of-the-art 3D reconstruction accuracy. Our CNN also shows the first competitive face recognition results on the face recognition benchmarks using 3D face shapes as representations, rather than the somewhat opaque deep features used by other systems. Finally, we introduce some additional techniques to push 3D face reconstruction to the next level, thereby estimating expression in 3d and also 3D fine-grained details of the face, aiming towards laser-scan quality in the wild.
Location: Charles Lee Powell Hall (PHE) - 223
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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Astani Civil and Environmental Engineering Ph.D. Seminar
Fri, Sep 29, 2017 @ 03:00 PM - 04:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Meida Chen and Sasan Tavakkol, Astani CEE Graduate Students
Talk Title: Point Cloud Meshes Segmentation and Information Extraction of Outdoor Scenes for The Creation of Virtual Environments and Simulation andInteractive and Immersive Coastal Hydrodynamic Simulation
Abstract: By Meida Chen
Be able to segment, classify, and recognize different types of objects and identify and extract associated features in a photogrammetric generated meshes is essential for creating realistic virtual simulations. Rendering different objects in a virtual environment differently and assign actual physical properties to each object will not only enhance the visual quality but also allow various user interaction with a terrain model. For instance, consider the case of training soldiers in a virtual environment with 3D meshes representing the scene. The task is to recognize the shortest path from location A to location B with the minimum exposure to enemy fire. With the artificial intelligence AI searching algorithm, such as A, the shortest path could be computed, and penalties cloud be assigned to a route based on the number of obstructions that are blocking the enemies line of sight. However, realistically speaking, line of sight that is blocked by buildings and trees should be assigned with different penalties when considering a route, since some materials are easy to be destroyed and damaged. Though this example is an oversimplification, it emphasizes the point that without segmented semantic data, realistic virtual simulations could not be achieved. Thus, in this study the authors established a mesh segmentation and information extraction framework that combines both supervised and unsupervised machine learning algorithms to analyze meshes point clouds that are generated with photogrammetric technique. The segmentation process will be first performed on the generated 3D point clouds. Following that, the generated meshes will be segmented accordingly. Object information such as individual tree locations, the dimension of a tree, and building footprints are then extracted separately. The proposed information extraction processes are designed to overcome the data quality issues in photogrammetric generated point clouds data tend to be noisy, and in some cases parts of a wall and the trunk of a tree cannot be captured due to dense canopy.
By Sasan Tavakkol
Recent catastrophic events such as the Tsunami in Japan 2011 and Hurricane Harvey storm surge and winds in the US 2017, have raised the global awareness for an urgent need to understand the response of developed coastal regions to tsunamis and wind waves. We discuss our efforts in developing the first interactive coastal wave simulation and visualization software, called Celeris. This software can significantly help scientists better understand nearshore wave dynamics as it allows them to observe wave interactions in real time, modify the boundary conditions and model parameters as the model is running, and see the effect of changes immediately. Celeris is released under a GNU license and is currently in use by hundreds of coastal researchers and engineering firms over the world. This software uses a hybrid finite volume finite difference method to solve the extended Boussinesq equations on the GPU. We also explore the opportunities in immersive visualization of coastal waves through Virtual Reality and Augmented Reality to help engineers work in an interactive, immersive, and collaborative environment.
Location: Waite Phillips Hall Of Education (WPH) - B27
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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Social: Tree of Knowledge Hike
Fri, Sep 29, 2017 @ 08:00 PM - 12:00 AM
Viterbi School of Engineering Student Organizations
Student Activity
Quickly becoming an iconic LA hiking destination, the Tree of Knowledge features stunning views of the downtown LA nightscape as well as the only surviving tree from the 2007 Hollywood Hills fires. Join ASBME Friday, September 29th as we make the night trek up to the tree and contribute to the famed geocaching box filled with inspirational stories, mesages, and quotes left by previous hikers. We will leave from campus at 8pm and don't forget a flashlight, water, snacks, good shoes, and a jacket.
Audiences: Everyone Is Invited
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Systems Security Engineering: Concepts and Overview Tutorial as Presented at 27th INCOSE International Symposium
Sat, Sep 30, 2017 @ 09:00 AM - 02:00 PM
Systems Architecting and Engineering, USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Mark Winstead, and Dr. Daryl Hild, MITRE Corporation
Talk Title: Systems Security Engineering: Concepts and Overview Tutorial as Presented at 27th INCOSE International Symposium
Series: INCOSE-LA Speaker Series
Abstract: System Security as a Design Problem (from NIST SP 800-160)
"Providing satisfactory security controls in a computer system is in itself a system design problem. A combination of hardware,software, communications, physical, personnel and administrative-procedural safeguards is required for comprehensive security. In particular, software safeguards
alone are not sufficient."
--The Ware Report
Defense Science Board Task Force on Computer Security, 1970.
Systems security engineering, as an integral part of systems engineering, applies scientific, mathematical, engineering, and measurement principles, concepts, and methods to coordinate, orchestrate, and direct the activities of various security engineering specialties and other contributing engineering specialties (e.g. reliability, safety and human factors) for the system of interest. This provides a fully integrated, system-level engineering perspective of system security. This tutorial will discuss an overview of Systems Security Engineering (SSE) as an increasingly critical part of Systems Engineering (SE).
SE is about meeting stakeholder needs. SSE is about meeting and ensuring sufficient protection of those stakeholder needs. The SSE activities include ensuring a system can function under adverse conditions associated with threats, disruptions and hazards (whether natural, e.g. weather, or man-made and whether malicious, misuse, or accidental). The SSE activities to protect stakeholder assets occur in all the life cycle phases (concept, development, production, utilization, support, and retirement). SSE as a discipline, as a role, as a set of activities across the life cycle to produce secure outcomes, and as a body of knowledge provide for meeting stakeholder protection needs. The tutorial will offer a system-oriented framing of the security perspective with connections to the methods and activities employed as part of a systems engineering project to address stakeholder security concerns.
Tutorial objectives:
--SSE as a Discipline: a specialty field and a branch of study in security foundations with open questions for potential research and development initiatives
--SSE as a Role: that is integrated with systems engineering and that leveraging security and other specialties
--SSE as an Activity: to plan, inform and achieve adequately secure outcomes via systems engineering processes as defined within INCOSE Systems Engineering Handbook
--SSE as a Body of Knowledge (BoK): that encompasses the history, vision, key terminology, and key concepts.
Directions:
The building is located on the northeast corner of Aviation and El Segundo Blvd. It is next to Big 5 Sporting Goods on El Segundo Blvd and Bimbo's Bakery on Aviation Blvd. There is plenty of parking assigned to the building. A MITRE host will meet attendees at the front door to let them into the building. If the MITRE host is not at the door upon arrival, they can be contacted at 310-297-8453. NOTE: Non-US Citizens will not be allowed to bring electronic devices due to facility security requirements.
Registration:
http://events.constantcontact.com/register/event?llr=l4ihvgeab&oeidk=a07eejljhycc2dcd102
Biography: Mark Winstead: Mark had over twenty-five years' STEM experience before joining the MITRE Corporation in 2014, including stints as a cryptologic mathematician, software engineer, systems engineer, systems architect and systems engineer in addition to being a systems security engineer. He has worked for several defense contractors, an Environmental Protection Agency contractor, a Facebook-like startup, a fabless semi-conductor manufacturer of commercial security protocol acceleration solutions, and a network performance management solutions company. Mark current works with various MITRE sponsors, helping programs with security engineering as well as teaming with others on integrating SSE into the acquisition systems engineering process. He also works with the MITRE Institute on developing materials for internal training courses for SSE. Mark is a graduate of the University of Virginia (PhD, Mathematics) and Florida State University (BS & MS, Mathematics). He resides in Colorado Springs, CO.
Daryl Hild: Daryl's career spans 3 decades helping warfighters with engineering solutions that span Army tactical communications networks, Army information technology network and systems management, NORAD/NORTHCOM air warning, NORAD/NORTHCOM missile warning, global positioning system, space systems, and cyberspace security. He currently serves as the Department Head for the Systems Security Engineering department within the MITRE Cyber Security Technical Center. Daryl previously served as Associate Department Head for the Combatant Commands and Air Force Space Command Security department. Within the Cyber Security Technical Center, he has collaborated with the MITRE Institute on developing a Systems Security Engineering (SSE) competency model and an SSE Learning Path. As well, Daryl is developing operational concepts and constructs for engineering defensive and offensive cybersecurity capabilities. Prior to MITRE, Daryl was an Army Signal Officer from 1984 to 1990. He received his bachelor degree in Electrical Engineering from Washington University, St. Louis, MO; and his master and doctoral degrees in Electrical and Computer Engineering from the University of Arizona, Tucson, AZ. In the community, Daryl serves as a BSA Venturing advisor enabling youth to develop leadership skills through community service projects and high adventure experiences.
Host: MITRE Corporation and INCOSE Los Angeles
More Information: Presentation1.jpg
Location: The MITRE Corporation, 2401 E. El Segundo BLVD, Suite 460, El Segundo, CA 90245.
Audiences: INCOSE Members $25; Nonmembers $45. Register now, limited to 24 attendees.
Contact: Deborah A. Cannon