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Biography, CV and Positions

Biography

Robert Freund is the Theresa Seley Professor in Management Science at the Sloan School of Management at MIT. He received his B.A. in Mathematics from Princeton University and M.S. and Ph.D. in Operations Research from Stanford University.

"I do research in large-scale optimization modeling, with an emphasis on continuous optimization, computational complexity, convexity, computational science, and related mathematical systems. My more recent interests include optimization issues in statistical and machine learning, data-driven optimization and decision-making, first-order methods for huge-scale problems, and sparse optimization."

Professor Freund has served as Co-Editor of the journal Mathematical Programming and as Associate Editor of several optimization and operations research journals. He received the Longuet-Higgins Prize in computer vision (2007).  He has received numerous teaching and education awards at MIT in conjunction with the MBA core course and textbook (co-authored with Dimitris Bertsimas) Data, Models, and Decisions: the Fundamentals of Management Science.

My Education

  • Ph.D. Operations Research, Stanford University, 1980
  • M.S. Operations Research, Stanford University, 1979
  • B.A. Mathematics, Princeton University , 1975
  • Program for Senior Executives, MIT, 1990

Current and Former Positions

  • Faculty Director, MIT Sloan MBA Program, 2021 – present
  • Deputy Dean for Faculty, Sloan School of Management, 2008-2011
  • Co-Director, MIT Program in Computation for Design and Optimization, 2004 - 2008
  • Co-Editor, Mathematical Programming (Series A), 1994 - 1999
  • Associate Editor, Mathematical Programming (Series A), 1999 - present
  • Associate Editor, Mathematical Programming (Series B), 1994 - 2003
  • Co-Director, MIT Operations Research Center, 1994-1998
  • Chair, INFORMS Optimization Section, 2001-2002
  • Chairman, Committee on the INFORMS Prize, 1993- 1994

My Research Interests

  • Nonlinear optimization theory, applications, and computation. Current focus: 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