Zhi Tian is a recognized expert in the fields of statistical signal processing, wireless communications, and machine learning. Specific areas of expertise have included detection and estimation theory, compressed sensing, decentralized network optimization and learning, statistical inference of network data, cognitive radio networks, MIMO systems, array processing, multi-target tracking, data fusion and Bayesian inference. Currently she conducts active research on both massive MIMO for 5G wireless networks and data science. For the latter, the research foci are on high-dimensional structured information processing, and on distributed machine learning in a network environment with sample efficiency, communication efficiency and robustness to privacy intrusion or cyber attacks.
Dr. Tian is a Fellow of the Institute of Electrical and Electronic Engineers (IEEE), the world’s largest technical professional organization for the advancement of technology. She has been actively involved with various IEEE activities in both the Signal Processing and Communications Societies. She served as an IEEE Distinguished Lecturer for both the IEEE Communications Society and the IEEE Vehicular Technology Society, and delivered technical tutorials on topics related to cognitive radios and compressed sensing in several international conferences. She has played leadership roles as Conference and Symposium Chair, and served as Associate Editor for both the IEEE Transactions on Wireless Communications and the IEEE Transaction on Signal Processing. She is a Member-at-Large of the IEEE Signal Processing Society Board of Governors (2019-2011).
Tian joined Mason after spending 14 years on the faculty of the Electrical and Computer Engineering department of Michigan Technological University, during which she also served a three-year term as Program Director for the Communications, Circuits and Sensing Systems program in the Division of Electrical Communications and Cyber Systems (ECCS) at the National Science Foundation.