Yonatan Mintz is an assistant professor in the Industrial and Systems Engineering department at the University of Wisconsin, Madison. His research focuses on the application of machine learning and automated decision making to human sensitive contexts. One application of his research has been on using patient level data, to create precision weight loss interventions that increase patient adherence. Yonatan is also interested in the sociotechnical implications of machine learning algorithms and has done work on fairness, accountability, and transparency in automated decision making. He is also interested in other aspects of personalized healthcare such as personalized drug dosing, neuro-degenerative disease progression monitoring, and mental resilience and psychological well being. In terms of methodology his research explors topics in machine learning theory, stochastic control, reinforcement learning, and nonconvex optimization.
Prior to joining UW–Madison, Yonatan was a postdoctoral research fellow at the department of Industrial and Systems Engineering at the Georgia Institute of Technology. Yonatan recieved his B.S. in Industrial and Systems Engineering with a concentration in Operations Research from Georgia Tech in 2012, and his Ph.D. in Industrial Engineering and Operations Research from the University of California, Berkeley in 2018. Between his undergraduate and graduate studies, Yonatan spent a year in industry working as a supply chain analyst at Caterpillar and as a data scientist at Google.