Ming Jin awarded faculty fellowship
Ming Jin, assistant professor of electrical and computer engineering in the College of Engineering at Virginia Tech, has been awarded the Shirish S. Sathaye Junior Faculty Fellowship in Electrical and Computer Engineering by the Virginia Tech Board of Visitors.
The Shirish S. Sathaye Junior Faculty Fellowship in Electrical and Computer Engineering was established with a generous gift from Shirish and Archana Sathaye. The creation of this fellowship enables the Bradley Department of Electrical and Computer Engineering at Virginia Tech to recognize and support outstanding junior faculty.
A member of the Virginia Tech community for more than five years, Jin’s research tackles one of the most critical challenges for artificial intelligence (AI): building systems that are intelligent, safe, and trustworthy in complex, real-world environments. In his Safe and Adaptive Generalizable Agent Lab, he develops AI that can thrive on uncertainty.
By combining reinforcement learning with formal methods from optimization and control theory, his group engineers systems with verifiable safety guarantees that can adapt without becoming unstable. The ultimate goal is to create "antifragile" systems for critical applications such as energy and cybersecurity that become more robust and reliable when faced with adversity.
His interdisciplinary approach has generated groundbreaking innovations in trustworthy artificial intelligence systems with applications in power and energy systems, cybersecurity, and machine learning.
Jin’s research has resulted in numerous publications in top-tier venues. His work has been recognized with prestigious awards, including first place in the CityLearn Challenge in 2021, the Amazon-Virginia Tech Initiative Research Award in 2023, and multiple best paper awards.
Jin has secured substantial external funding exceeding $5.3 million with a personal share of over $2.1 million. He was awarded the inaugural National Science Foundation’s Safe Learning-Enabled Systems grant.
Jin consistently receives exceptional teaching evaluations, develops and teaches key courses in machine learning and optimization and mentors a diverse group of graduate and undergraduate students.
Jin received his bachelor’s degree from Hong Kong University of Science and Technology and a Ph.D. from University of California, Berkeley. He completed postdoctoral work in the Department of Industrial Engineering and Operations Research at the University of California, Berkeley.
