John E. Swearingen Professor, Chemical Engineering
Professor Nick Sahinidis received his Diploma in Chemical Engineering from the Aristotle University of Thessaloniki, Greece in 1986 and his Ph.D. in Chemical Engineering from Carnegie Mellon University, Pittsburgh, Pennsylvania in 1990.
Between 1991 and 2007, he served on the faculty of the University of Illinois at Urbana, initially as an Assistant Professor and Associate Professor of Mechanical and Industrial Engineering and later as an Associate Professor and Professor of Chemical and Biomolecular Engineering. In 2007, he moved to Carnegie Mellon University, where he is now John E. Swearingen Professor of Chemical Engineering.
He has served on the editorial boards of many journals, including Industrial & Engineering Chemistry Research, Journal of Global Optimization, Mathematical Programming Computation, Optimization and Engineering, Optimization Letters, and Optimization Methods and Software. He has also served in numerous positions within INFORMS (Institute for Operations Research and the Management Sciences) and AIChE (American Institute of Chemical Engineers). He is currently the programming chair of the CAST division of AIChE.
His doctoral advisees have become members of the faculty at major research universities, including Georgia Institute of Technology and Purdue University, and leading industrial laboratories, including those of American Airlines, BPAmoco, and ExxonMobil.
EducationPh.D., 1990, Carnegie Mellon
Diploma, 1986, Aristotle University of Thessaloniki, Greece
Professor Sahinidis concentrates on optimization in biology, chemistry, medicine, and engineering.
Informatics Problems in Chemistry, Biology, and Medicine
With the recent accumulation of vast amounts of chemical, biological, and clinical data, many scientific fields are becoming increasingly data-driven as opposed to model-driven. This paradigm shift has brought about many challenging computational problems. Even though these problems originate from very disparate fields, they have very similar mathematical structures. In particular, they involve the use of a merit function to evaluate alternatives from very large, typically combinatorial, search spaces. Professor Sahinidis’ work in this area provides comprehensive and rigorous solutions to inverse imaging problems in X-ray crystallography, modeling and estimation of dynamic metabolic and signaling pathways, structural bioinformatics, medical diagnosis and prognosis, and the design of novel chemicals that are environmentally benign. A recent focus of data-centric work in Professor Sahinidis’ group has been the ALAMO project, which addresses the problem of discovering algebraic relationships that are hidden in a set of data, an experimental process, or a simulation model.
Optimization Theory, Algorithms, and Software
A plethora of problems in science and engineering require the solution of nonlinear optimization problems with multiple local solutions. Professor Sahinidis’ research has recently led to the development of an all-purpose, rigorous global optimization methodology. His results have included the development of a unifying framework for domain reduction; a theory of convex extensions that provides strong relaxations for a variety of mathematical programs; an entirely linear outer-approximation scheme for global optimization problems; finite branching schemes for certain continuous nonconvex problem classes; and the global optimization software BARON. Scientists and engineers have used the BARON software in many application areas, including the development of new Runge-Kutta methods for partial differential equations, energy policy making, modeling and design of metabolic processes, product and process design, engineering design, and automatic control. The ultimate goal of this research thrust is to provide precise and valuable computational optimization tools that will allow engineers and scientists to solve problems that are currently considered intractable. Towards this end, projects pursue fundamental advances in linear and nonlinear optimization, and the development of advanced computing technologies for optimization.
The Sahinidis research group at CMU has consistently involved over 15 graduate students and postdoctoral researchers.
Professor Sahinidis is currently the Director of the Center for Advanced Process Decision-making (CAPD) which comprises over 20 companies.
Awards and Honors
- 2016 National Award and Gold Medal by HELORS
- 2015 Constantin Carathéodory Prize
- 2014 Fellow of the Institute for Operations Research and Management Sciences
- 2012 Steven J. Fenves Award, Carnegie Mellon University
- 2010 CAST Division Computing in Chemical Engineering Award
- 2008 Named to John E. Swearingen Chair, Carnegie Mellon University
- 2006 Beale-Orchard-Hays Prize, Mathematical Programming Society
- 2006 Bayer Lectureship, Carnegie Mellon University
- 2005-2008 University Scholar, University of Illinois
- 2005 Center for Advanced Study Associate, University of Illinois
- 2004 INFORMS Computing Society Prize
- 1999 AIChE CAST Director’s Award
- 1998 NSF/Lucent Technologies Industrial Ecology Fellowship
- 1995 NSF CAREER Award
Cozad, A., N. V. Sahinidis and D. C. Miller, Learning surrogate models for simulation-based optimization, AIChE Journal, 60, 2211-2227, 2014.
Khajavirad, A. and N. V. Sahinidis, Convex envelopes generated from finitely many compact convex sets, Mathematical Programming, 137, 371-408, 2013.
Vouzis, P. and N. V. Sahinidis, GPU-BLAST: Using graphics processors to accelerate protein sequence alignment, Bioinformatics, 27, 182-188, 2011.
Tawarmalani, M. and N. V. Sahinidis, A polyhedral branch-and-cut approach to global optimization, Mathematical Programming, 103, 225-249, 2005.
Shectman, J. P. and N. V. Sahinidis, A finite algorithm for global minimization of separable concave programs, Journal of Global Optimization, 12, 1-36, 1998.