• Optimization under uncertainty
• Markov decision processes
• Robust optimization
• Incentive design
• Healthcare operations 
• Health policy

Prior to joining the University of Minnesota, Saumya Sinha was a postdoctoral scholar at Rice University, working with Prof. Andrew Schaefer in the areas of optimization and organ transplantation. Before to that, Sinha received a Ph.D. in applied mathematics under the supervision of Prof. Archis Ghate at the University of Washington, Seattle. Her research focuses on problems of sequential decision-making and optimization under uncertainty, motivated primarily by applications in healthcare operations, health policy and inventory control.

More information can be found on Sinha's personal website.

Education

Ph.D., University of Washington, Seattle, 2018
Applied Mathematics (minor in Advanced Data Science)
Thesis: Robust dynamic optimization: theory and applications

M.S., University of Washington, Seattle, 2015
Applied Mathematics

M.S., Tata Institute of Fundamental Research - Centre for Applicable Mathematics, 2013
Mathematics

B.S. (Honors), St. Stephen's College, University of Delhi, 2011
Mathematics

Selected Publications

A. Dunbar, S. Sinha, A.J. Schaefer. "Relaxations and duality for multiobjective integer programming," submitted to Mathematical Programming. Finalist for the INFORMS Undergraduate Operations Research Prize, 2020.

S. Sinha, A. Ghate. "Approximate policy iteration for robust countable-state Markov decision processes," under second review at Operations Research.

D. Mildebrath, T. Lee, S. Sinha, A.J. Schaefer, A.O. Gaber. "Characterizing rational transplant program response to outcome-based regulation," to appear in Operations Research. (preprint)

S. Sinha, A. Ghate. "Policy iteration for robust nonstationary Markov decision processes," Optimization Letters, Vol 10(8), 1613-1628, 2016. (preprint)

S. Sinha, J. Kotas, A. Ghate. "Robust response-guided dosing," Operations Research Letters, Vol 44(3), 394-399, 2016. (link)