Webinar Link: https://usc.zoom.us/webinar/register/WN_zyIBh_1gQLmKpMJG0GyLxw 

Abstract:  Ubiquitous sensing, wireless communication and distributed computation have transformed the way we interact with the physical world. While we celebrate the convenience and the improved quality of life having smart devices around us, the data collection practices have moved from remote fields to private living environments and workspaces; and data collected have also shifted from non-sensitive scientific data to personal, sensitive data that is closely related to the user's health conditions, emotional states, physical activities and social relationships. In this talk I will review some of our recent work on protecting privacy of sensitive data by minimalist-style sensing and targeted data perturbation, as well as fundamental challenges/impossibility results regarding data privacy and utility.

Biography:  Professor Jie Gao is currently Professor in Department of computer science, Rutgers University. She was on the faculty of Computer Science department at Stony Brook University from 2005-2019. She received B.Eng from the Special Class of the Gifted Young, University of Science and Technology of China in 1999, Ph.D in Computer Science from Stanford University in 2004 and was a postdoc at Caltech from 2004-2005. She received the NSF career award in 2006, IMC best paper award (2009), EWSN best paper award (2021) and multiple Research Excellence Awards in computer science department of Stony Brook. She is currently serving on the editorial board of ACM Transactions on Sensor Networks, International Journal of Computational Geometry and Applications and IEEE Transactions on Network Science and Engineering. She published over 140 referred papers in computer networking and theoretical computer science fields, and has graduated 17 Ph.D students.

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Hosts: Pierluigi Nuzzo and Bhaskar Krishnamachari

Center for Cyber-Physical Systems and the Internet of Things (CCI) http://cci.usc.edu

Center for Autonomy and AI (AAI) https://aai.usc.edu