Van Hentenryck’s research on privacy focuses on applied differential privacy for complex applications in mobility, energy, and other areas. The key focus is on isolating differential privacy techniques that are accurate enough for sophisticated analytic tasks, including optimization and machine learning.


  • OptStream: Releasing Time Series Privately. Ferdinando Fioretto, Terrence W.K. Mak, Pascal Van Hentenryck, Journal of Artificial Intelligence Research (JAIR), to appear.
  • Privacy-Preserving Obfuscation of Critical Infrastructure Networks. Fernandino Fioretto, Terrence Mak, and Pascal Van Hentenryck. In the Proceedings of 28th Inter- national Joint Conference on Artificial Intelligence (IJCAI-19), Macao, China, 2019.
  • Privacy-Preserving Federated Data Sharing. Fernandino Fioretto and Pascal Van Hentenryck.  In the Proceedings of 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019), Montreal, Canada, 2019.
  • Differential Privacy for Power Grid Obfuscation, Ferdinando Fioretto, Terrence W.K. Mak, Pascal Van Hentenryck, arXiv:1901.06949 [cs.AI].