**Robert Vanderbei** is a Professor in the Department of
Operations Research and Financial Engineering
at Princeton University. From 2005 to 2012, he was chair
of the department. In addition, he holds courtesy appointments in the
Departments of
Mathematics,
Astrophysics,
Computer Science, and
Mechanical and Aerospace Engineering.
He is also a member of the
Program in Applied and Computational Mathematics,
is a founding member of the
Bendheim Center for Finance,
and a former Director of the
Engineering and Management Systems Program.

Beyond Princeton, he is a Fellow of the American Mathematical Society (AMS), the Society for Applied and Industrial Mathematics (SIAM) and the Institute for Operations Research and the Management Sciences (INFORMS). Within INFORMS, he has served as President of the Optimization Society and the Computing Society and is the 2017 winner of the Khachiyan Prize for his work in optimization. He also serves on the Advisory Board for the journal Mathematical Programming Computation.

He has degrees in Chemistry (BS), Operations Research and Statistics (MS), and Applied Mathematics (MS, PhD). After receiving his PhD from Cornell (1981), he was an NSF postdoc at the Courant Institute for Mathematical Sciences (NYU) for one year, then a lecturer in the Mathematics Department at the University of Illinois-Urbana/Champaign for two years before joining Bell Labs in 1984. At Bell Labs he made fundamental contributions to the field of optimization and holds three patents for his inventions. In 1990, he left Bell Labs to join Princeton University where he has been since.

In addition to hundreds of
research papers, he has written three books: (i) a textbook entitled
*Linear Programming:
Foundations and Extensions* now in its fourth edition and published
by Springer, (ii) *Sizing Up The Universe*,
an introductory astronomy
book written jointly with J. Richard Gott and published by National Geographic,
and (iii)
*Real and Convex Analysis*,
a textbook written jointly with Erhan Cinlar and published by Springer.