报告人：Miao Pan，Assistant Professor

Department of Electrical and Computer Engineering

University of Houston

Dr. Miao Pan is an Assistant Professor in the Department of Electrical and Computer Engineering at University of Houston. He was a recipient of NSF CAREER Award in 2014. Dr. Pan received Ph.D. degree in Electrical and Computer Engineering from University of Florida in August 2012. Dr. Pan's research interests include cognitive radio networks, underwater communications and networking, cyber-physical systems, and cybersecurity. He has published 50 plus papers in prestigious journal and magazine papers including IEEE/ACM Transactions on Networking, IEEE Journal on Selected Areas in Communications, IEEE Transactions on Mobile Computing, and IEEE Transactions on Smart Grid, and 75 papers in top conferences such as IEEE INFOCOM, ICDCS, and IEEE IPDPS. His work won Best Paper Awards in Globecom 2017 and Globecom 2015, respectively. Dr. Pan was an Associate Editor for IEEE Internet of Things (IoT) Journal from 2015 to 2018.

报告内容：The cyber-physical system (CPS) is largely referred to as the next generation of engineered systems with the integration of communication, computation, and control to achieve the goals of stability and efficiency for physical systems. Cyber-physical systems are often collect huge amounts of information for data analysis and decision making. The collection of information helps the system make smart decisions through advanced data processing, computing or learning algorithms. However, there always lies a question: How "big" can be regarded as big data? Besides, data collection may lead to an undesirable loss of privacy for the participating users, thereby putting their promised benefits at risk. To address those issues, we have made some efforts to effectively utilize the collected data via data-driven approach while preserving the differential privacy of the users who contribute their data.

In today's talk, we will present two of our recent works on big data differential privacy preservation for cyber-physical systems: i) data-driven caching with users' local differential privacy in information-centric networks; and ii) data-driven optimization for utility providers with differential privacy of users' energy profile in smart grid.

时间：2018年7月30日 上午9:00-11:30

地点：best365网页版登录官方网站千佛山校区创新大厦416室

承办单位：best365网页版登录官方网站控制科学与工程学院