Stan Uryasev

Professor and Frey Family Endowed Chair of Quantitative Finance
 
Dr. Stan Uryasev profile picture
Dept. of Applied Math & Statistics
Stony Brook University
Math Tower, Room B-148
Stony Brook, NY 11794-3600
 
Tel:  (631) 632 5470
Fax: (631) 632 8490
Email:  Stanislav.Uryasev@stonybrook.edu
 

 

Stan Uryasev received his M.S. in Applied Mathematics from the Moscow Institute of Physics and Technology (MIPT), Russia, in 1979 and Ph.D. in Applied Mathematics from the Glushkov Institute of Cybernetics, Kiev, Ukraine in 1983. From 1979 to 1987 he held a research position at the Glushkov Institute. From 1988 to 1992 he was a Research Scholar at the International Institute for Applied System Analysis, Luxenburg, Austria. From 1992 to 1998 he held the Scientist position at the Risk and Reliability Group, Brookhaven National Laboratory, Upton, NY. From 1998 to 2019 he was the George and Rolande Willis Endowed Professor at the University of Florida, and the director of the Risk Management and Financial Engineering Lab.

His research and teaching interests include quantitative finance, risk management, stochastic optimization, machine learning, and military operations research. See Google Scholar for the list of the most cited publications, https://scholar.google.com/citations?hl=en&user=Uwg1zpkAAAAJ. Here is the full list of publications.

His joint paper with Prof. Rockafellar on Optimization of Conditional Value-At-Risk in The Journal of Risk, Vol. 2, No. 3, 2000  is among the 100 most cited papers in Finance. Many risk management/optimization packages implemented the approach suggested in this paper (MATLAB implemented a toolbox).​

The important theoretical contribution presenting a unified scheme for portfolio optimization, statistical estimation, risk management, and utility theory: Rockafellar R.T. and S. Uryasev. The Fundamental Risk Quadrangle in Risk Management, Optimization, and Statistical Estimation. Surveys in Operations Research and Management Science, 18, 2013.

Collaborative research with industry has been documented in the library of Case Studies containing Portfolio Safeguard (PSG) codes, data, and calculation results in Text, MATLAB, and R environments. See the list of Case Studies in Financial Engineering, Advanced Statistics and other areas.