Mingyan Liu () is a Chinese-American electrical engineer who has been serving as the 17th dean of the University of Michigan College of Engineering since May 2026. At the College of Engineering, she served as the associate dean for academic affairs from June 2023 to May 2026 and as the 15th chair of the Electrical and Computer Engineering Division from September 2018 to May 2023.
Liu's fields of research are in optimal resource allocation, sequential decision theory, incentive design, online learning, modeling and mining of large scale Internet measurement data concerning cyber security.
Biography Liu completed her high school education at Nanjing Foreign Language School in Nanjing, Jiangsu, China, in 1991.
She received a bachelor's degree with a major in electrical engineering from the Nanjing University of Aeronautics and Astronautics in 1995. She traveled to the United States, and received a Master of Science in systems engineering in 1997 and a Doctor of Philosophy in electrical engineering in 2000 from the University of Maryland, College Park.
University of Michigan After receiving her doctorate, Liu joined the faculty of the University of Michigan College of Engineering as an assistant professor in 2000. She was appointed as an associate professor in September 2006 and as a full professor in September 2012.
Liu served as the chair of Electrical and Computer Engineering (ECE) Division at the EECS Department from September 2018 to May 2023. After that, she served as the associate dean for academic affairs of the College of Engineering from June 2023 to May 2026.
On April 28, 2026, Liu was appointed as the 17th dean of the College of Engineering, effective May 15, 2026, with her three-year term set to expire on July 31, 2029.
Academic research
Liu studies optimization, sequential decision and learning theory, game theory, and incentive mechanisms. She applies these methods to large-scale networked systems, cybersecurity, and cyber-risk quantification. Her early work focused on wireless, mobile ad hoc, and sensor networks. It addressed resource allocation, performance modeling, and energy efficiency.
Liu later used Internet-scale measurements and machine learning to study cybersecurity risk. A 2014 paper found a statistically significant correlation between network mismanagement and malicious activity. A 2015 study used 258 externally observable network features to forecast reported security incidents.
She has also studied cyber insurance as an incentive mechanism. Her 2021 book, Embracing Risk, argues that insurance can support risk reduction by aligning cybersecurity incentives. It also covers interdependent risks, underwriting, and data-driven risk assessment.
Awards and honors Liu received multiple awards and honors from the University of Michigan:
2011 EECS Department Outstanding Achievement Award 2015 College of Engineering Excellence in Education Award 2017 College of Engineering Monroe-Brown Foundation Service Excellence Award 2018 Distinguished University Innovator 2026 Rackham Graduate School Distinguished Graduate Mentoring Award
She also received multiple awards and honors from other institutions:
IEEE Fellow (2014) "Crossing the Valley of Death" PI Excellence Award (2016), United States Department of Homeland Security ECE Department Distinguished Alumni Award (2017), University of Maryland, College Park IEEE Communications Society Distinguished Lecturer (2026–2027)
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