Graduate program Stochastic Systems Analysis and Optimization
The Department of Mathematical Sciences at Stevens offers an interdisciplinary graduate program in Stochastic Systems to educate students in the area of analysis and optimal decisions for complex systems involving uncertain data. This unique program combines analysis of uncertainty and risk with modern decision tools as stochastic optimization and stochastic optimal control.
Full information and course description
Supervision of PhD students
Master Theses supervised at Stevens Institute of Technology
- Mingsong Ye - graduated August 2017
Thesis: Conditional Stochastic Dominance for Two-stage-extended Problem
Currently PhD student at Stevens Institute of Technology
- Constantine A. Vitt - graduated May 2017
Thesis: Risk-Averse Radiation Therapy Design via Stochastic Order Constraints and Risk Functionals
Currently Senior Data Scientist at Honeywell
- Nolan Sandberg - graduated February 2013
Thesis: Stochastic-Orders Approach to Radiation Therapy Design.
Currently Software Engineer at Facebook
- Gregory J. Stock - graduated February 2008
Thesis: Testing stochastic dominance by mean-risk inequalities: power of the tests.
Currently Visiting Assistant Professor at Lehigh University
- Thomas Surowiec - graduated May, 2006
Thesis: Stability of Stochastic Optimization Problems with Stochastic Dominance Constraints.
Currently Associate Professor at Philipps-University Marburg, Germany