Yonatan Mintz

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Yonatan Mintz is a Postdoctoral Research Fellow in the Stewart School of Industrial and Systems Engineering at Georgia Tech. He received his M.S. and Ph.D. from the University of California Berkeley in 2014 and 2018, respectively.

Yonatan's research focuses on using stochastic optimization and machine learning techniques to create personalized systems that better serve individuals. A primary application of his research has been on using patient level data, to create precision weight loss interventions that increase patient adherence. Some of this work was then incorporated into the Cal Fitness app which received coverage in the Daily Californian, Berkeley Engineer, and on the main Berkeley Engineering site . Yonatan is also interested in the application of these techniques in sustainability, and their impact of fairness, accountability, and transparency. In terms of methodology his research has also explored topics in machine learning, stochastic control, reinforcement learning, and nonconvex optimization.

Yonatan received his bachelor's degree in Industrial and Systems Engineering with a concentration in Operations Research from Georgia Tech in 2012 and graduated with highest honors. Between his undergraduate studies and graduate school he worked at both Google  and Caterpillar.  During his PhD he has also had the privilege of mentoring students and working with the Phillipines California Advanced Research Institutes.

Expertise:
  • Machine Learning
  • Personalized Healthcare
  • Reinforcement Learning and Stochastic Control
  • Optimization
Finalist, Health Application Society Pierskalla Best Paper Award October 2017
Grassi Fellowship August 2017-December 2017
IEOR Department Fellowship August 2013- August 2014
Honorable Mention, INFORMS Undergraduate Operations Research Prize October 2012