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Events for the 1st week of October
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Center for Systems and Control (CSC@USC) and Ming Hsieh Institute for Electrical Engineering
Mon, Oct 02, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Aaron Ames, California Institute of Technology
Talk Title: Unified Control of Dynamic Robotic Systems
Series: Fall 2017 Joint CSC@USC/CommNetS-MHI Seminar Series
Abstract: Humans have the ability to locomote with deceptive ease, navigating everything from daily environments to uneven and uncertain terrain with efficiency and robustness. With the goal of achieving these capabilities on robotic systems, this talk will present a unified formal framework for realizing dynamic behaviors in an efficient, provably correct and safety-critical fashion, along with the application of these ideas experimentally on a wide variety of robotic systems. In particular, we will introduce an optimization-based control framework that is able to dynamically balance control objectives and safety constraints for dynamic robotic systems. These concepts will be illustrated through their application to the humanoid robot DURUS, with the result being dynamic and efficient locomotion displaying the hallmarks of natural human walking: heel-toe behavior. The translation of these ideas to robotic assistive devices, and specifically powered prostheses, will be described in the context of custom-built hardware. Finally, the extension of these concepts to safety-critical systems-”including automotive applications, multi-agent systems, and swarms of quadrotors-”will be discussed.
Biography: Aaron D. Ames is the Bren Professor of Mechanical and Civil Engineering and Control and Dynamical Systems at the California Institute of Technology. Prior to joining Caltech, he was an Associate Professor in Mechanical Engineering and Electrical & Computer Engineering at the Georgia Institute of Technology. Dr. Ames received a B.S. in Mechanical Engineering and a B.A. in Mathematics from the University of St. Thomas in 2001, and he received a M.A. in Mathematics and a Ph.D. in Electrical Engineering and Computer Sciences from UC Berkeley in 2006. He served as a Postdoctoral Scholar in Control and Dynamical Systems at Caltech from 2006 to 2008, and began is faculty career at Texas A&M University in 2008. At UC Berkeley, he was the recipient of the 2005 Leon O. Chua Award for achievement in nonlinear science and the 2006 Bernard Friedman Memorial Prize in Applied Mathematics. Dr. Ames received the NSF CAREER award in 2010, and is the recipient of the 2015 Donald P. Eckman Award recognizing an outstanding young engineer in the field of automatic control. His research interests span the areas of robotics, nonlinear control and hybrid systems, with a special focus on applications to bipedal robotic walking-”both formally and through experimental validation. His lab designs, builds and tests novel bipedal robots, humanoids and prostheses with the goal of achieving human-like bipedal robotic locomotion and translating these capabilities to robotic assistive devices.
Host: Mihailo Jovanovic
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
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Towards Mobile Emoji Prediction from Speech and Textual Captions
Tue, Oct 03, 2017 @ 02:30 PM - 05:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
University Calendar
Bio:
Luis Marujo is a Research Scientist at Snap Inc. Prior to joining the Snap Research team in 2016, he completed his dual-degree Ph.D. in Language Technologies ('15) from Carnegie Mellon University (CMU) and the Instituto Superior Técnico (IST), Portugal. He also obtained a MSc. ('12) in Language Technologies from CMU. He holds MSc. ('09) and BSc. ('07) in Computer Science and Engineering from IST. He was awarded the best poster award at the S3MR 2011.
Abstract:
Emojis are very popular ideograms used to either concisely communicate or complement the information of a text with an emotion or visual concept. Emojis are mainly use on mobile devices due to the availability of intuitive emoji keyboards. They are very popular in social media, but they have not been explored from a Speech Processing point of view. In this work, we investigate mobile-friendly multimodal approaches that use audio, speech, and textual captions to predict emojis in public video Snaps. The key idea of pipeline is to translate the input signals into text and keywords in order to conduct the analysis in a textual space. Our emoji prediction pipeline includes speech transcription, keyword spotting and dictionary based classification.
In addition we use music detection and language identification to filter the content. Our experimental results indicate that our approach using speech transcription or a list of pre-selected words from keyword spotting provide comparable information to what is found in textual captions for emoji prediction. This is an important result as it allows us to suggest emojis to snap videos before the user starts typing a caption. Our initial results also indicate that combining both textual captions with speech output can improve emoji recommendation results beyond using only textual captions.Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Benjamin Paul
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New EE PhD Welcome Happy Hour
Tue, Oct 03, 2017 @ 05:00 PM - 07:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Student Activity
Welcome New EE PhDs! Join us for a casual Happy Hour to meet other new EE PhDs, advisors, MHI, and have lots of fun!
RSVP Here: https://mhiee.wufoo.com/forms/z1cw2opg0mhqz3m/
Date: Oct. 3rd, 2017
Time: 5-7pm
Place: Bacaro LA
2308 S Union Ave
Los Angeles, CA 90007
University ParkLocation: Bacaro LA
Audiences: New EE PhD Students
Contact: Benjamin Paul
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Cross-listed between CCI-MHI Joint Seminar Series on Cyber-Physical Systems and CSC@USC Seminar Series
Wed, Oct 04, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Carolyn Beck, University of Illinois at Urbana-Champaign
Talk Title: Epidemic Processes Over Topologically Varying Networks
Abstract: The study of epidemic processes has been a topic of interest for many years over a wide range of areas, including mathematical systems, biology, physics, computer science, social sciences and economics. More recently, there has been a resurgence of interest in the study of epidemic processes focused on the spread of viruses over networks, motivated not only by recent devastating outbreaks of infectious diseases, but also by the rapid spread of opinions over social networks, and the security threats posed by computer viruses. Most of the models considered in these recent studies have been focused on network models with static network structures, however almost all systems being considered have inherently dynamic structures. In this talk, we will discuss the modeling of epidemic processes over topologically varying networks, and present stability analysis results which elucidate the behavior of these systems. Specifically, we will derive conditions that guarantee convergence to the disease free equilibrium under varying assumptions on the networks and disease process parameters. Simulation results and potential control actions will be presented and discussed to conclude the talk.
Biography: Carolyn L. Beck is a faculty member in the College of Engineering at the University of Illinois, Urbana-Champaign, in the Department of Industrial and Systems Engineering. She completed her Ph.D. at Caltech, her M.S. at Carnegie Mellon, and her B.S. at Cal Poly, all in Electrical Engineering. Prior to completing her Ph.D., she was an R&D engineer at Hewlett- Packard in Santa Clara. Carolyn has held visiting faculty positions at the Royal Institute of Technology (KTH) in Stockholm, Stanford University, and Lund University in Lund, Sweden.
She was the recipient of an NSF CAREER award and an ONR Young Investigator award, as well as local teaching awards. Her research interests range from network inference problems to control of anesthetic pharmacodynamics and include mathematical systems theory, model reduction and approximation for the purpose of analysis and control design, and clustering and aggregation methods.
Host: Ketan Savla, ksavla@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos