Mingxi Liu
Assistant Professor
Dr. Mingxi Liu is an Assistant Professor with the Department of Electrical & Computer Engineering at the University of Utah. His broad research interests include control theory, optimization, and cyber-security, and their applications in power systems, renewable energy systems, smart grid, and cyber-physical systems.
Before joining the University of Utah, Dr. Liu was an NSERC Postdoc Fellow at the University of California, Berkeley, working with Professor Duncan Callaway. He obtained his Ph.D. and M.A.Sc degrees from the Department of Mechanical Engineering at the University of Victoria, Canada in 2016 and 2012, respectively. He received B.Eng. degree in Control Sciences and Engineering from Harbin Institute of Technology, China in 2010.
Dr. Liu received the NSF CAREER Award in 2022. He is currently a Member of IEEE. He serves as Associate Editor for IEEE Canadian Journal of Electrical and Computer Engineering and the IEEE Open Journal of the Industrial Electronics Society. He also serves in the Young Editorial Board of Advances in Applied Energy. In 2022, Dr. Liu became a member of Nááts'íilid Initiative.
Dr. Liu's CV can be found here. For more information about Dr. Liu, please visit his personal website.
Xiang Huo
Ph.D. Candidate
Xiang Huo (since Fall 2019): Before joining the University of Utah, Xiang obtained his Bachelor’s and Master’s degrees from Harbin Institute of Technology, China. He is now working on developing new algorithms to address scalability and privacy in large-scale cooperative multi-agent optimizations. His research is supported in part by the US Department of Energy.
Mahan Fakouri Fard
Ph.D. Student
Mahan Fakouri Fard (since Summer 2021): Before joining the University of Utah, Mahan obtained his Bachelor’s and Master’s degree from the University of Tehran, Iran. He is now working on hardware hardening strategies for distribution network resilience enhancement and data-driven methods for for-purpose cyber-attack detection and mitigation in distribution/decentralized optimizations.