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Robert M. Freund

I support and stand with people who are not of my race — in the academic community and elsewhere — in protest against hate, brutality, divisiveness, fear, indifference, inequality, and discrimination.

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's website can be found here.)

Publications/Talks/Collaborators
Robert Freund, Professor in Management Science

New Online Course: Data Science and Analytics

MIT xPRO: Professional Certificate in Data Science and Analytics

Taught by Profs. Freund, Farias, Levi, and Ramakrishnan

Three Recent Papers

"Using Taylor-approximated Gradients to Improve the Frank-Wolfe Method for Empirical Risk Minimization", with Zikai Xiong, submitted. For additional results and extensions, see [link].

"Analysis of the Frank-Wolfe Method for Convex Composite Optimization involving a Logarithmically-Homogeneous Barrier", with Renbo Zhao, to appear in Mathematical Programming A.

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

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