Robert Freund is the Theresa Seley Professor in Management Science at the MIT Sloan School of Management. He conducts research in large-scale optimization – both applied and theoretical – as well as related mathematical systems. Freund teaches MBA courses in business analytics and quantitative methods, as well as advanced courses in optimization theory. Freund is the co-author, along with Dimitris Bertsimas, of the MBA textbook* Data, Models, and Decisions: the Fundamentals of Management Science. Bio and CV can be found here.*

(You may also be looking for my name-fellow and colleague, Daniel Freund. His website can be found here.)

### Three Recent Papers

"An 'Oblivious' Ellipsoid Algorithm for Solving a System of (In)Feasible Linear Inequalities," with Jourdain Lamperski and Michael Todd, to appear in *Mathematical Programming.*

"Condition Number Analysis of Logistic Regression, and its Implications for Standard First-Order Solution Methods" Freund, R.M., Paul Grigas, and Rahul Mazumder, *submitted.*

"Generalized Stochastic Frank-Wolfe Algorithm with Stochastic “Substitute” Gradient for Structured Convex Optimization." Lu, Haihao, and Robert M. Freund, to appear in *Mathematical Programming.*

### Research Interests

- Nonlinear optimization theory, applications, and computation -- current focus on algorithmic theory and practice of first-order methods
- Computational complexity of nonlinear optimization
- Interior-point methods in convex optimization
- Computational science
- Related mathematical systems
- Applied optimization in management and engineering
- Linear optimization
- Fixed-point methods