Research Interests
I am interested in the development and analysis of quantitative optimization models under uncertainty. Stochastic optimization models are used in many areas such as economics, finance, engineering, and energy systems. Realistic models have a large number of variables, and multiple interactions across time and space. Advanced computational methods, and analytical approximations that take advantage of problem structure are needed in order to analyze realistic models. I am interested in both the development of computational methods and applications.
Computational Methods:
- Multiscale modeling and algorithms
- Decomposition algorithms
- Robust Optimization
- Global Optimization
- Nonlinear programming
- Decentralized decision making
Application areas:
- Energy systems
- Chemical engineering
- Policy Analysis
- Economics
- Finance
- Statistical Inference
Address: