AI Seminar: Emily Mower Provost and Arunesh Sinha
Emily Mower Provost / Arunesh Sinha
Human Behavior Understanding and Engineering: A Partnership / AI for safety and security
Tuesday, November 08, 2016|
4:00pm - 5:15pm
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About the Event
Emily Mower Provost's Abstract As our speech processing technologies continue to advance we see increasing enthusiasm for using these technologies in an assistive capability. I also highlight our ongoing speech-based assistive technology research, estimating speech quality for individuals with aphasia. I will describe our interactive tablet-based software, which is based on picture description tasks, illustrate how we have used this platform to collect a new dataset of aphasic and healthy speech, and demonstrate how these data can be processed using automatic speech recognition (ASR) techniques. We have demonstrated that we can use ASR tools to automatically estimate speech quality at levels comparable to an average human evaluator. Finally, I will touch briefly on our work classifying mood for individuals with bipolar disorder using naturally collected cell phone data. Arunesh Sinha's Abstract In any security setting, defenders are beset with the problem of limited resources. Optimal allocation of limited defense resources is an important issue for many defense agencies. Recognizing the fact that a defender-adversary interaction is inherently a game, I will present my past work on game theoretic models for optimal defense resource allocation in an adversarial environment. I will talk about two projects: a project in collaboration with TSA that introduced a game model for screening of passengers and provided novel optimization methods to compute the equilibrium and another project that provided a machine learning based crime prediction tool for the University of Southern California police. I will also briefly mention about my ongoing work on adversarial learning.
Emily Mower Provost's Bio Emily Mower Provost is an Assistant Professor in Computer Science and Engineering at the University of Michigan. She received her B.S. in Electrical Engineering (summa cum laude and with thesis honors) from Tufts University, Boston, MA in 2004 and her M.S. and Ph.D. in Electrical Engineering from the University of Southern California (USC), Los Angeles, CA in 2007 and 2010, respectively. She is a member of Tau-Beta-Pi, Eta-Kappa-Nu, and a member of IEEE and ISCA. She has been awarded the National Science Foundation Graduate Research Fellowship (2004-2007), the Herbert Kunzel Engineering Fellowship from USC (2007-2008, 2010-2011), the Intel Research Fellowship (2008-2010), the Achievement Rewards For College Scientists (ARCS) Award (2009 – 2010), and the Oscar Stern Award for Depression Research (2015). She is a co-author on the paper, "Say Cheese vs. Smile: Reducing Speech-Related Variability for Facial Emotion Recognition," winner of Best Student Paper at ACM Multimedia, 2014. She is also a co-author of the winner paper of the Classifier Sub-Challenge event at the Interspeech 2009 emotion challenge. Her research interests are in human-centered speech and video processing, multimodal interfaces design, and speech-based assistive technology. The goals of her research are motivated by the complexities of human emotion generation and perception. Arunesh Sinha's Bio Arunesh Sinha is an Assistant Research Scientist in the Computer Science and Engineering Department at the University of Michigan. Prior to joining University of Michigan, he was a postdoctoral scholar in the Computer Science Department at the University of Southern California. He received his Ph.D. from Carnegie Mellon University. Arunesh has conducted research at the intersection of security, machine learning and game theory. His interests lie in the theoretical aspects of multi-agent interaction, machine learning, security and privacy, along with an emphasis on the real-world applicability of the theoretical models. He was awarded the Bertucci fellowship at CMU in appreciation of his novel research. His paper was nominated for the best application paper at AAMAS 2016. He chairs two of the leading workshops at the intersection of AI and computer security: AISec and AICS.
Open to: Public