Bart Van Parys

Email : vanparys@mit.edu

I am an assistant professor in the operations research and statistics group at the MIT Sloan School of Management. My research is located on the interface between optimization and machine learning. In particular, I develop novel mathematical methodologies and algorithms with which we can turn data into better decisions. Although most of my research is methodological, I do enjoy applications related to problems in renewable energy.

Recent Publications

• Liu, Z., B.P.G. Van Parys, and H. Lam (2023). “Smoothing $f$-divergence distributionally robust optimization: Rate optimality and complexity independence”. In: SIAM Journal on Optimization. Submitted. Link

• Bennouna, M.A. and B.P.G. Van Parys (2022). “Holistic robust data-driven decisions”. In: Mathematical Programming. Submitted. Finalist for 2023 INFORMS Data Mining Best Paper Award Competition. Link

• Bennouna, M.A., R. Lucas, and B.P.G. Van Parys (2023). “Certified robust neural networks: Generalization and corruption resistance”. In: International Conference on Machine Learning (ICML). Honolulu, Hawaii, USA, pp. 2092–2112. Link

• Wang, I., C. Becker, B.P.G. Van Parys, and B. Stellato (2022). “Mean robust Optimization”. In: Mathematical Programming. Major Revision. Won the 2022 INFORMS Computing Society Student Paper Prize. Link

• Das Gupta, S., B.P.G. Van Parys, and E.K. Ryu (2023). “Branch-and-bound performance estimation programming: A unified methodology for construction optimal optimization methods”. In: Mathematical Programming. Appeared also in Quanta Magazine. Link

Interests

I am always interested in students or collaborators interested in working on

• Optimization Algorithms
• Robust Analytics
• Statistical Efficiency