Pascal Van Hentenryck

A. Russell Chandler III Chair and
Professor

Contact

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Education

  • Joint Sc.B. and M.S. Computer Science (1985), University of Namur, Belgium
  • Ph.D. Computer Science (1987), University of Namur, Belgium

About

Pascal Van Hentenryck is an A. Russell Chandler III Chair and Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech, the director of the NSF AI Institutes for Advances in Optimization, and the director of Tech AI at Georgia Tech. Prior to this appointment, he was a professor of Computer Science at Brown University for about 20 years, he led the optimization research group (about 70 people) at National ICT Australia (NICTA) (until its merger with CSIRO), and was the Seth Bonder Collegiate Professor of Engineering at the University of Michigan. 

Van Hentenryck is a Fellow of AAAI (the Association for the Advancement of Artificial Intelligence) and INFORMS (the Institute for Operations Research and Management Science). He has been awarded two honorary doctoral degrees from the University of Louvain and the university of Nantes, the IFORS Distinguished Lecturer Award, the Philip J. Bray Award for teaching excellence in the physical sciences at Brown University, the ACP Award for Research Excellence in Constraint Programming, the ICS INFORMS Prize for Research Excellence at the Intersection of Computer Science and Operations Research, and an NSF National Young Investigator Award. He received a Test of Time Award (20 years) from the Association of Logic Programming and numerous best paper awards, including at IJCAI and AAAI. Van Hentenryck has given plenary/semi-plenary talks at the International Joint Conference on Artificial Intelligence (twice), the International Symposium on Mathematical Programming, the SIAM Optimization Conference, the Annual INFORMS Conference, NeurIPS, and many other conferences. Van Hentenryck was program co-chair of the AAAI’19 conference, a premier conference in Artificial Intelligence. Van Hentenryck is a pioneer of constraint programming and the fusion of AI and Optimization. He is the author of 5 books and editors of 4 others. 

Research

Van Hentenryck’s research focuses in Artificial Intelligence and Operations Research. His current focus is to develop AI methodologies, algorithms, and systems for addressing challenging problems in  energy systems, supply chains and manufacturing, health care systems, mobility systems, and corporate systems. He is particularly interested in the fusion of AI and Optimization to solve problems that are not tractable by either technologies alone, and trustworthy AI in general. In the past, his research focused on optimization and the design and implementation of innovative optimization systems, including the CHIP programming system (a Cosytec product), the foundation of all modern constraint programming systems and the optimization programming language OPL (an IBM Product). Van Hentenryck has also worked on computational biology, numerical analysis, and programming languages, publishing in premier journals in these areas.

Teaching

Van Hentenryck teaches classes in constraint programming, optimization, and AI. He has designed four levels of Seth Bonder summer camps for middle- and high-school students every summer, ranging from introduction to computing, data science, deep learning, and agentic AI. Van Hentenryck has won the Philip J. Bray Award at Brown University in 2010, the Teaching Excellence Award for Online Teaching at Georgia Tech in 2021, and the Student Recognition of Excellence in Teaching: Class of 1934 Award at Georgia Tech in 2021, 2022, and 2023. He also designed a widely successful MOOC in discrete optimization on Coursera (for about 12 years). 

Awards and Honors

  • A. Russell Chandler III Chair, Georgia Institute of Technology 2018
  • Fellow of the INFORMS (Institute for Operations Research and Management Science). 2016
  • Seth Bonder Collegiate Professor, University of Michigan 2016
  • Richard Newton Research Excellence Award, NICTA. 2015
  • Test of Time Award (20 years): Association of Logic Programming. 2014
  • IFORS Distinguished Lecturer, Minneapolis, Minnesota. 2013
  • Ulam Fellow, Center for NonLinear Studies, Los Alamos. 2012
  • Doctor Honoris Causa, the University of Nantes 2011
  • Philip J. Bray Award for teaching excellence in the physical sciences, Brown University. 2010
  • Fellow of the Association for the Advancement of Artifical Intelligence (AAAI). 2009
  • Doctor Honoris Causa, University of Louvain, Belgium. 2008
  • ACP Award for Research Excellence in Constraint Programming 2006
  • IBM Faculty Award. 2004
  • INFORMS Computing Society (ICS) Award for research excellence at the intersection of computer science and operations research. 2002
  • NSF National Young Investigator Award 1993

Representative Publications

Books

  1. Ferdinando Fioretto and Pascal Van Hentenryck Differential Privacy in Artificial Intelligence: From Theory to Practice, Boston-Delft: now publishers, (2025), http://dx.doi.org/10.1561/9781638284772.
  2. P. Van Hentenryck and L. Michel. Constraint-Based Local Search. The MIT Press, Cambridge, MA, 2009. (Paperback version of [6]).
  3. P. Van Hentenryck and R. Bent. Online Stochastic Combinatorial Optimization. MIT Press, 2009. (Paperback version of [5]).
  4. P. Van Hentenryck and R. Bent. Online Stochastic Combinatorial Optimization. Prentice Hall/India, 2007. (Reprint of [5]).
  5. P. Van Hentenryck and R. Bent. Online Stochastic Combinatorial Optimization. The MIT Press, Cambridge, MA, 2006.
  6. P. Van Hentenryck and L. Michel. Constraint-Based Local Search. The MIT Press, Cambridge, MA, 2005.
  7. P. Van Hentenryck. The OPL Optimization Programming Language. The MIT Press, Cambridge, MA, 1999.
  8. P. Van Hentenryck, L. Michel, and Y.Deville. Numerica: A Modeling Language for Global Optimization. The MIT Press, Cambridge, MA, 1997.
  9. P. Van Hentenryck. Constraint Satisfaction in Logic Programming. The MIT Press, Cambridge, MA, 1989

Recent Journal Articles

  1. Mingjian Tuo, Xingpeng Li, and Pascal Van Hentenryck Machine Learning-assisted Dynamics-Constrained Day-Ahead Energy Scheduling. Electric Power Systems Re-
    search, to appear, 2025.
  2. Lucas Kletzander, Tommaso Mazzoli, Nysret Musliu, and Pascal Van Hentenryck. Integrating Column Generation and Large Neighborhood Search for Bus Driver Schedul-
    ing with Complex Break Constraints. Journal of Artificial Intelligence Research, to appear, 2025.
  3. Hongzhao Guan, Beste Basciftci, and Pascal Van Hentenryck. Bilevel Optimization and Heuristics for Transit Network Design with Latent Demand. Transportation
    Science, to appear, 2025.
  4. Jorge Huertas, and Pascal Van Hentenryck. Parallel Batch Scheduling With Incompatible Job Families Via Constraint Programming IEEE Transactions on Semiconductor Manufacturing, to appear, 2025.
  5. Jorge Huertas, and Pascal Van Hentenryck. A Constraint Programming Model For Serial Batch Scheduling With Minimum Batch Size. Operations Research Perspectives,
    to appear, 2025.
  6. Tinghan Ye, Amira Hijazi, and Pascal Van Hentenryck. Contextual Stochastic Optimization for Omnichannel Multi-Courier Order Fulfillment Under Delivery Time Uncertainty. INFORMS MSOM (Manufacturing & Service Operations Management), to appear, 2025
  7. Andrew Rosemberg, Francois Pacaud, Joaquim Dias Garcia, Robert B. Parker, Kaarthik Sundar, Russell Bent, and Pascal Van Hentenryck. Strategic Bidding in Energy Markets with Gradient-Based Iterative Methods. Sustainable Energy, Grids and Networks, July 2025 (Online).
  8. Jiawei Lu, Tinghan Ye, Wenbo Chen, Pascal Van Hentenryck. Boosting Column Generation with Graph Neural Networks for Joint Rider Trip Planning and Crew Shift Scheduling. Transportation Research Part E, (to appear), 2025.
    Ritesh Ojha, Wenbo Chen, Hanyu Zhang, Reem Khir, Alan Erera, Pascal Van Hentenryck. Outbound Load Planning in Parcel Delivery Service Networks using
    Machine Learning and Optimization. Transportation Science, (to appear), 2025.
  9. Lesia Mitridati, Jalal Kazempour, and Pascal Van Hentenryck. Electricity-Aware Bid Format for Coordinated Heat and Electricity Market Clearing. ACM SIGENERGY Energy Informatics Review, Volume 5, Issue 3, September 2025.
  10. Hanyu Zhang, Reza Zandehshahvar, Mathieu Tanneau, and Pascal Van Hentenryck. Weather-Informed Probabilistic Forecasting and Scenario Generation in Power Systems. Applied Energy, Volume 384, April 15, 2025.
  11. Seonho Park and Pascal Van Hentenryck. Self-Supervised Learning for Large-Scale Preventive Security Constrained DC Optimal Power Flow. IEEE Transactions on Power Systems, 40(3), 2205-2216, May 2025.
  12. Pascal Van Hentenryck. Constraint Programming. Revue Ouverte d’Intelligence Artificielle, 5(2–3), 139–159, 2024.
  13. Guancheng Qiu, Mathieu Tanneau, and Pascal Van Hentenryck. Dual conic proxies for AC optimal power flow. Electric Power Systems Research 236, 110661, November 2024.
  14. H. Zhang, M. Tanneau, C. Huang, V.R. Joseph, S. Wang, P. Van Hentenryck. Asset bundling for hierarchical forecasting of wind power generation. Electric Power Systems Research 235, 110771, October 2024.
  15. M. Klamkin, M. Tanneau, T. Mak, P Van Hentenryck. Bucketized Active Sampling for learning ACOPF. Electric Power Systems Research 235, 110697, October 2024.
  16. K. Wu, M. Tanneau, P. Van Hentenryck. Strong mixed-integer formulations for trans- mission expansion planning with FACTS devices. Electric Power Systems Research 235, 110695, October 2024.
  17. A. Rosemberg, M. Tanneau, B. Fanzeres, J. Garcia, P. Van Hentenryck Learning Optimal Power Flow value functions with input-convex neural networks. Electric Power Systems Research 235, 110643, October 2024.
  18. W. Chen, M. Tanneau, P. Van Hentenryck Real-time risk analysis with optimization proxies. Electric Power Systems Research 235, 110822, October 2024,
  19. Chungjae Lee, Kevin Dalmeijer, and Pascal Van Hentenryck. Optimizing Autonomous Transfer Hub Networks: Quantifying the Potential Impact of Self-Driving
    Trucks. EURO Journal on Transportation and Logistics (to appear).

2025 Conference Publications

  1. Steven Berguin and Pascal Van Hentenryck. Self-Supervised Airfoil Shape Optimization. AIAA SciTech, Orlando, FL, January 12-16, 2026.
  2. Sikai Cheng, Amira Hijazi, Jeren Konak, Alan Erera, and Pascal Van Hentenryck. SPOT: Spatio-temporal Pattern Mining and Optimization for Load Consolidation in Freight Transportation Networks. IEEE International Conference on Data Mining (ICDM-2025), Washington DC, USA. November 12-15, 2025. (11% Acceptance Rate).
  3. Tinghan Ye, Amira Hijazi and Pascal Van Hentenryck Conformal Predictive Distributions for Order Fulfillment Time Forecasting. Joint International Conference on Computational Logistics. September 8-10, 2025, Delft University, The Netherlands.
  4. Vladimir Dvorkin, Ferdinando Fioretto, Pascal Van Hentenryck, Pierre Pinson, and Jalal Kazempour Privacy-Preserving Convex Optimization: When Differential Privacy Meets Stochastic Programming 64th IEEE Conference on Decision and Control, Rio de Janeiro, Brazil, December 10-12, 2025.
  5. Hongzhao Guan, Paul Riggins, Tyler Simko, Jasmine Mangat, Cassandra Moe, Urooj Haider, Frank Pantano, Effie G. McMillian, Genevieve Siegel-Hawley, Pascal Van Hentenryck, and Nabeel Gillani. A community-driven optimization framework for redrawing school attendance boundaries. The fifth ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO’25), Pittsburgh, PA, USA, November 5–7, 2025.
  6. Lesia Mitridati, Jalal Kazempour, and Pascal Van Hentenryck. Electricity-Aware Bid Format for Coordinated Heat and Electricity Market Clearing. 14th DACH+ Conference on Energy Informatics, Aachen, Germany, September 2025.
  7. Alireza Moradi, Mathieu Tanneau, Reza Zandehshahvar, and Pascal Van Hentenryck. Enhanced Renewable Energy Forecasting and Operations through Probabilistic Forecast Aggregation. Proceedings of the IISE Annual Conference & Expo 2025, Atlanta, May-June, 2025.
  8. Guancheng Qiu, Mathieu Tanneau, and Pascal Van Hentenryck. Dual Conic Proxy for Semidefinite Relaxation of AC Optimal Power Flow. Proceedings of the IISE Annual Conference & Expo 2025, Atlanta, May-June, 2025.
  9. Michael Klamkin, Mathieu Tanneau, and Pascal Van Hentenryck. Dual Interior Point Optimization Learning. Proceedings of the IISE Annual Conference & Expo 2025, Atlanta, May-June, 2025.
  10. Fan Jiang, Xingpeng Li, and Pascal Van Hentenryck. A Deep Neural Network-based Frequency Predictor for Frequency-Constrained Optimal Power Flow. IEEE IAS Annual Meeting, New Taipei, Taiwan, Jun. 2025.
  11. Andrew Rosemberg, Francois Pacaud, Joaquim Dias Garcia, Robert B. Parker, Kaarthik Sundar, Russell Bent, and Pascal Van Hentenryck. Strategic Bidding in Energy Markets with Gradient-Based Iterative Methods 12th Bulk Power System Dynamics and Control Symposium (IREP 2025), Sorrento, Italy, June 22-27, 2025
  12. Thomas Bruys, Reza Zandehshahvar, Amira Hijazi and Pascal Van Hentenryck. Confidence-Aware Deep Learning for Load Plan Adjustments in the Parcel Service Indudtry. AAAI Bridge Program Combining AI and OR/MS for Better Trustworthy Decision Making, Thirty-Nine AAAI Conference on Artificial Intelligence (AAAI-25), Philadelphia, PA, February 25 – March 4.