Research in machine learning focuses on deep constrained learning, learning for complex energy networks, learning in mobility and social systems, and interpretable machine learning.
Recent Publications
- Combining Deep Learning and Optimization for Preventive Security-Constrained DC Optimal Power Flow. Alexandre Velloso and Pascal Van Hentenryck. IEEE Transactions on Power Systems (to appear).
- Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach. Cuong Tran, Ferdinando Fioretto, and Pascal Van Hentenryck. AAAI-2021, February 2021.
- High-Fidelity Machine Learning Approximations of Large-Scale Optimal Power Flow, Minas Chatzos, Ferdinando Fioretto, Terrence W.K. Mak, Pascal Van Hentenryck, arXiv:2006.16356, June 2020.
- Real-Time Dispatching of Large-Scale Ride-Sharing Systems: Integrating Optimization, Machine Learning, and Model Predictive Control. Connor Riley, Pascal Van Hentenryck, and Enpeng Yuan. In the Proceedings of 29th International Joint Conference on Artificial Intelligence (IJCAI-20), Tokyo, Japan 2020.
- Prediction and Behavioral Analysis of Travel Mode Choice: A Comparison of Machine Learning and Logit Models. Xiang Yan, Xilei Zhao, Alan Yu, Pascal Van Hentenryck. Travel Behaviour and Society. (to appear).
- Lagrangian Duality for Constrained Deep Learning. Ferdinando Fioretto, Pascal Van Hentenryck, Terrence W.K. Mak, Cuong Tran, Federico Baldo and Michele Lombardi. In the Proceedings of 2020 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Ghent, Belgium, September 2020.
- Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods. Ferdinando Fioretto, Terrence W.K. Mak, and Pascal Van Hentenryck. Proceeding of The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20).
- Distilling Black-Box Travel Mode Choice Model for Behavioral Interpretation. Xilei Zhao, Zhengze Zhou, Xiang Yan, Pascal Van Hentenryck. In the 2020 Transportation Board Annual Meeting, January 2020.
- Expecting to be HIP: Hawkes Intensity Processes for Social Media Popularity. M.-A. Rizoiu, L. Xie, S. Sanner, M. Cebrian, H. Yu, and P. Van Hentenryck. In the Proceedings of The 26th International World Wide Web Conference, Perth, Australia. April 3–7, 2017.
- Rapid assessment of disaster damage using social media activity. Yury Kryvasheyeu, Haohui Chen, Nick Obradovich, Esteban Moro, Pascal Van Hentenryck, James Fowler, Manuel Cebrian. Science Advances. 2(3), March, 11, 2016.
- Performance of Social Network Sensors During Hurricane Sandy Yury Kryvasheyeu, Caron Chen, Esteban Moro, Pascal Van Hentenryck, Manuel Cebrian
PLOS One, 10(2), February, 2015.