Robert M. Freund

Robert M. Freund is the Theresa Seley Professor in Management Science at the MIT Sloan School of Management, specializing in Operations Research. His research focuses on nonlinear optimization, computational complexity, and first-order methods with applications in management and engineering. He holds a PhD in Operations Research from Stanford University and has authored influential textbooks like Data, Models, and Decisions: The Fundamentals of Management Science.

• Education: B.A. in Mathematics (Princeton, 1975), M.S. and Ph.D. in Operations Research (Stanford, 1979–1980).
• Roles: Faculty Director of MIT Sloan MBA Program, Deputy Dean for Faculty (2008–2011), Co-Director of MIT Program in Computation for Design and Optimization (2004–2008).

His research interests span optimization theory, computational science, and applications in machine learning. Notable contributions include advancements in Frank-Wolfe algorithms, interior-point methods, and photonic crystal design. He has received the Longuet-Higgins Prize (2007) and multiple teaching awards.

Recent work includes the development of restarted PDHG algorithms, Taylor-approximated gradients for empirical risk minimization, and analysis of first-order methods' computational guarantees. His collaborative efforts with students and researchers like Zikai Xiong and Haihao Lu have produced impactful publications in Mathematical Programming and SIAM Journal on Optimization.

Freund has also contributed to educational initiatives, including MIT's Professional Certificate in Data Science and Analytics. His work bridges theoretical optimization advancements with practical applications in engineering and data-driven decision-making.