معرفی
Mingxi Zhu is an Assistant Professor in the Information Technology Management group at the Scheller College of Business, Georgia Institute of Technology. He holds a Ph.D. from Stanford Graduate School of Business in Operations, Information & Technology, where he was co-advised by Professors Haim Mendelson and Yinyu Ye. His academic journey includes a Master's in Economics from Duke University and dual Bachelor's degrees in English Literature and Economics from Beijing Foreign Studies University.
Education:
- Ph.D., Operations, Information & Technology, Stanford Graduate School of Business
- M.A., Economics, Duke University
- B.A., English Literature, Beijing Foreign Studies University
- B.Ec., Economics, Beijing Foreign Studies University
Mingxi's research centers on multi-agent collaborated learning, focusing on optimization algorithms, economics, and mechanisms in federated learning environments. His work spans machine learning, data sharing policies, information acquisition, and applications in online finance and auctions. He investigates how distributed agents can effectively learn and make decisions collectively, particularly under constraints of privacy, information asymmetry, and strategic behavior.
His recent publications and projects address topics such as randomization in ADMM algorithms, benefits of minimal data sharing in distributed learning, pitfalls of Shapley values in federated learning, and dynamic pricing in large networks. These works reflect a strong trend toward algorithmic design, economic mechanisms, and empirical analysis in digital platforms, combining theoretical rigor with practical relevance.
Scientific Awards and Fellowships:
- Best Paper Award, NeurIPS Workshop (2022)
- Institutional Venture Partners Fellowship (2020–2021)
- David S. Tappan Jr. Fellowship (2019–2020)
- Robert J. and Doreen D. Marshall Scholarship (2018–2019)
- George A. and Barbara C. Jedenoff Fellowship (2017–2018)
Mingxi has served as an instructor for courses including Information System & Digital Transformation and Special Issues of Information Systems at Georgia Tech. He has also been a Teaching Assistant at Stanford for optimization and electronic business courses. He has advised undergraduate students in research and diversity programs and has provided peer review services for top journals such as Management Science and Mathematics of Operations Research. His service includes board membership in the Stanford GSB Greater China Business Club and participation in diversity and inclusion initiatives.
He is actively engaged in research that bridges computer science, economics, and business, with ongoing work in federated learning mechanisms, information disclosure in auctions, and dynamic pricing. His projects often involve collaboration with leading scholars and have practical implications for online platforms and financial systems.
