Patrick Jaillet

Dugald C. Jackson Professor in EECS, Co-Director of the Operations Research Center

Email:

Research Interests:

Online Optimization and Learning, Machine Learning, Decision Making Under Uncertainty

Dr. Patrick Jaillet is the Dugald C. Jackson Professor in the Department of Electrical Engineering and Computer Science and a member of the Laboratory for Information and Decision Systems at MIT. He holds a joint appointment in the Operation Research and Statistics Group at MIT Sloan. He is also co-Director of the MIT Operations Research Center and the Faculty Director of the MIT-France program. He was Head of Civil and Environmental Engineering at MIT from 2002 to 2009, where he currently holds a joint appointment. From 1991 to 2002 he was a professor at the University of Texas in Austin, the last five years as the Chair of the Department of Management Science and Information Systems within the McCombs School of Business School. He co-founded and was Director of UT Austin's Center for Computational Finance. Before his appointment in Austin, he was a faculty and a member of the Center for Applied Mathematics at the Ecole Nationale des Ponts et Chaussee in Paris. He received a Diplome d'Ingenieur from France (1981), and then came to MIT where he received an SM in Transportation (1982) followed by a PhD in Operations Research (1985).
Dr. Jaillet's research interests include online optimization and learning; machine learning; and decision making under uncertainty. His research is funded by US federal sources such as NSF, ONR, AFOSR, and internationally by Singapore. Professor Jaillet's teaching covers subjects such as machine learning; algorithms; mathematical programming; network science and models; and probability. Dr. Jaillet's consulting activities primarily focus on the development of optimization-based analytic solutions in various industries, including defense, financial, electronic marketplace, and information technology.
Dr. Jaillet's research interests include online optimization and learning; machine learning; and decision making under uncertainty. His research is funded by US federal sources such as NSF, ONR, AFOSR, and internationally by Singapore. Professor Jaillet's teaching covers subjects such as machine learning; algorithms; mathematical programming; network science and models; and probability. Dr. Jaillet's consulting activities primarily focus on the development of optimization-based analytic solutions in various industries, including defense, financial, electronic marketplace, and information technology.

Research Clusters:

Website:

Google Scholar:

Operations Research and Statistics, Networks and Systems, Behavior and Demand Modeling, Automation, Control and Artificial Intelligence, Economics and Finance

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