Steimle’s research interests include operations research and data analytics with applications in public health and medical decision making. She has methodological interests in sequential decision-making, decision-making under uncertainty, and computational optimization with a focus on Markov decision processes and stochastic programming. She has worked on projects studying preventive treatment related to cardiovascular disease and diabetes, as well as vaccination decisions for the control of norovirus.

She received her Ph.D. and M.S.E. in industrial and operations engineering from the University of Michigan and her B.S. in systems science and engineering from Washington University in St. Louis. Steimle received a National Science Foundation Graduate Student Research Fellowship and the Ford Foundation Predoctoral Fellowship Honorable Mention. In 2017, she was a member of the third-place team in the New England Journal of Medicine’s SPRINT Data Challenge.

Steimle is a member of INFORMS and has served on the INFORMS Subdivisions Council.