Embedded Files
Affiliation
Associate Professor, Michigan State University
Trustworthy AI for decision-making under uncertainty
I develop statistically grounded AI and predictive modeling methods for high-stakes decision problems under uncertainty, with applications in insurance, finance, and risk analytics. My work focuses on uncertainty quantification, representation learning, and modeling for settings where reliability, transparency, and defensible decisions matter.
Education
PhD, University of Wisconsin-Madison
Associate member (ASA) of the Society of Actuaries
About
I am an Associate Professor in the Actuarial Science Program at Michigan State University, with affiliations in the Department of Statistics and Probability and the Department of Mathematics. My research lies at the intersection of actuarial science, statistics, machine learning, and decision analytics.
My broader goal is to build trustworthy AI methods for decision-making under uncertainty: methods that do not merely predict well, but also provide insight into uncertainty, support transparent reasoning, and perform reliably in regulated or high-consequence environments.
Research themes
My current research themes and links to publications can be found on the research page.
Talks & activities
A list of my talks and activities can be found on the talks & activities page.
Teaching
A summary of my teaching can be found on the teaching page.
For students
If you are an undergraduate student interested in research experience, please see my undergraduate students page.
If you are a current/prospective MS or PhD student with an interest in working with me, then please see my MS/PhD students page.
Contact information
Gee Y. Lee
Email: leegee@msu.edu
Office telephone: (517)353-6332
Office location: C337 Wells Hall, 619 Red Cedar Rd, East Lansing, 48824, MI.
Please use the navigation bar at the top in order to navigate this website!
Google Sites
Report abuse