Dr. Jaillet's research interests include online optimization and learning; machine learning; and sequential decision making under uncertainty. His research has been supported by US federal sources, such as NSF, ONR, AFOSR; the private sector, such as IBM, Microsoft, Google; and internationally by Singapore NRF. Professor Jaillet's teaching covers subjects such as machine learning; algorithms; optimization; 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 financial, electronic marketplace, and information technology.
Dr. Jaillet was a fulbright scholar in 1990 and the recipient of many research and teaching awards. He is a Fellow of the Institute for Operations Research and Management Science Society (INFORMS), a member of the Mathematical Optimization Society (MOS), and a member of the Society for Industrial and Applied Mathematics (SIAM). He is currently an Associate Editor for INFORMS Journal on Optimization, Networks, and Naval Research Logistics, and has been an Associate Editor for Operations Research from 1994 until 2005 and for Transportation Science from 2002 until 2017.