Gary C. Butler Family Chair and
Professor
Education
- Ph.D. Chemical Engineering (1990), Carnegie Mellon University
- Diploma Chemical Engineering (1986), Aristotle University
About
Nick Sahinidis is the Gary C. Butler Family Chair and Professor in the H. Milton Stewart School of Industrial and Systems Engineering and the School of Chemical and Biomolecular Engineering at Georgia Tech. His current research activities are at the interface between computer science and operations research, with applications in various engineering and scientific areas, including: theory, algorithms, and software for global optimization of mixed-integer nonlinear programs; informatics problems in chemistry and biology; process and energy systems engineering. Sahinidis has served on the editorial boards of many leading journals and in various positions within AIChE (American Institute of Chemical Engineers). He is the current Editor-in-Chief of Mathematical Programming Computation. He has also served on numerous positions within INFORMS (Institute for Operations Research and the Management Sciences), including Chair of the INFORMS Optimization Society. He received an NSF CAREER award, the INFORMS Computing Society Prize, the Beale-Orchard-Hays Prize from the Mathematical Optimization Society, the Computing in Chemical Engineering Award, the Constantin Carathéodory Prize, and the National Award and Gold Medal from the Hellenic Operational Research Society. Sahinidis is a member of the U.S. National Academy of Engineering and a fellow of AIChE and INFORMS.
Research
Professor Sahinidis conducts research at the interface of optimization, machine learning, and computational science. He has made seminal contributions to mixed-integer nonlinear optimization, sparse model discovery, and data-driven optimization of complex systems. He has deployed his algorithms to solve a wide range of problems in (bio)molecular engineering, energy systems, and supply chains.
Teaching
Professor Sahinidis teaches mathematical optimization, process systems engineering, and scientific computing. He has developed a bioinformatics M.S. program and has taught courses ranging from thermodynamics and metabolic engineering to approximation algorithms and GPU computing.
Representative Publications
Kuznetsov, A. and N. V. Sahinidis, Nonconvex optimization problems involving the Euclidean norm: Challenges, progress, and opportunities, SIAM Review, accepted, 2025.
Oh, D., S. Kim, C. A. R. Perini, J.-P. Correa-Baena and N. V. Sahinidis, Algorithm-guided experimentation for optimization of high-performance perovskite solar cells, ACS Energy Letters, 10, 6037-6046, 2025.
Zhang, Y. and N. V. Sahinidis, Solving continuous and discrete nonlinear programs with BARON, Computational Optimization and Applications, 92, 1123-1161, 2025.
Ma, K., L. M. Rios, A. Bhosekar, N. V. Sahinidis and S. Rajagopalan, Branch-and-Model: A derivative-free global optimization algorithm, Computational Optimization and Applications, 85, 337-367, 2023.
Cozad, A. and N. V. Sahinidis, A global MINLP approach to symbolic regression, Mathematical Programming, 170, 97-119, 2018.
Austin, N., N. V. Sahinidis, I. Konstantinov and D. W. Trahan, COSMO-based computer-aided molecular/mixture design: A focus on reaction solvents, AIChE Journal, 64, 104-122, 2018.
Rios, L. M. and N. V. Sahinidis, Derivative-free optimization: A review of algorithms and comparison of software implementations, Journal of Global Optimization, 56, 1247-1293, 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, Global optimization of mixed-integer nonlinear programs: A theoretical and computational study, Mathematical Programming, 99, 563-591, 2004.
Sahinidis, N. V., Optimization under uncertainty: State-of-the-art and opportunities, Computers & Chemical Engineering, 28, 971-983, 2004.