Patrick Jaillet - Research

Please contact me directly if you are interested in one of these activities and/or in some recent publications.

main interests these days:

online and data-driven optimization problems
dynamic and real-time optimization in networks
applications: internet, transportation, energy, finance

research group:


Maximilien Burq, doctoral student, MIT ORC, 2014-now
Jie Chen, post-doc, SMART, Singapore, 2013-now
Arthur Flajolet, doctoral student, MIT ORC, 2013-now
Virgile Galle, doctoral student, MIT ORC, 2013-now
Chong Yang Goh, doctoral student, MIT ORC, 2012-now
Swati Gupta, doctoral student, MIT ORC, 2011-now
Nikita Korolko, doctoral student, MIT ORC, 2012-now
Meghna Lowalekar, doctoral student, SMU, Singapore, 2015-now
Sebastien Martin, doctoral student, MIT ORC, 2014-now
Konstantina Mellou, doctoral student, MIT ORC, 2014-now
Phong Nguyen, doctoral student, NUS CS, Singapore, 2013-now
Anatoliy Prokhorchuk, doctoral student, NTU EE, Singapore, 2016-now
Julia Romanski, doctoral student, MIT ORC, 2016-now
Haibin Yu, doctoral student, NUS CS, Singapore, 2014-now


Dawsen Hwang, doctoral student, MIT EECS, 2011-16 (now Google, Chicago)
Andrew Johnston, master student, MIT LGO-EECS, 2014-16
Kfir Yeshayahu, master student, MIT LGO-EECS, 2014-16
Le Nguyen Hoang, post-doc, MIT, 2015
Sanjay Jena, post-doc, SMART, Singapore, 2014-15 (now, UQAM Montreal, Canada)
Setareh Borjian, master student, MIT CEE & ORC, 2012-15 (now, Oracle)
Ali Oran, post-doc, SMART, Singapore, 2011-15
Maokai Lin, doctoral student, MIT ORC, 2009-15 (now, Smarking, California)
Yiyin Ma, master student, MIT LGO-EECS, 2013-15
Andrew Mastin, doctoral student, MIT EECS, 2010-15 (now Lawrence Livermore National Laboratory)
Yossiri Adulyasak, post-doc, SMART, Singapore, 2013-14 (now, HEC Montreal, Canada)
Vahideh Manshadi, post-doc, MIT EECS and ORC, 2011-14 (now, Yale University)
Augusta Niles, master student, MIT LGO-EECS, 2012-14 (now, Amazon Robotics, Massachusetts)
Thibaut Vidal, post-doc, MIT EECS and ORC, 2013-14 (now, PUC, Rio de Janeiro, Brazil)
Xin Lu, doctoral student, MIT ORC, 2009-13 (now, Amazon, Seattle)
Rico Zenklusen, post-doc, MIT EECS and Math, 2011-12 (now, ETH Zurich, Switzerland)
Brian Crimmel, master student, MIT ORC/Draper, 2010-12 (now, U.S. Coast Guard Academy)
Jacob Cates, master student, MIT ORC/Draper, 2009-11 (now, Navy)

research interns

Seyed Hossein Hashemi Doulabi, Ecole Polytechnique Montreal, MIT EECS, 3/2015-8/2015 (now, PhD, Ecole Polytechnique, Montreal)
Baptiste Roziere, Ecole Normale Superieur Lyon, SMART, Singapore, 1/2015-7/2015
Maximilien Burq, Ecole Polytechnique Paris, MIT EECS, 4/2014-8/2014 (now, MIT ORC doctoral program)
Yee Sian Ng, NUS, SMART 6/2013-5/2014 (now, MIT ORC doctoral program)
Chen Yao Liu, NUS, SMART 6/2012-8/2012 (now, Lehigh University)
Alexandre Hollocou, Ecole Polytechnique Paris, MIT EECS 4/2012-8/2012 (now, Corps des Mines, France)
Pierre Jeremie, Ecole Polytechnique Paris, MIT EECS, 3/2011-6/2011 (now, Corps des Mines, France)
Thibault Lehouillier, ENSIMAG, MIT EECS, 2/2011-8/2011 (now, PhD, Ecole Polytechnique, Montreal)
Antoine Legrain, Ecole Centrale de Paris, MIT EECS, 1/2011-7/2011 (now, PhD, Ecole Polytechnique, Montreal)

current research projects:

Below are some specific topics that could each lead to the definition of several research topics of interests for either interns/urops, graduate students, and/or postdocs.
1. Online Resource Allocation Problems: Motivated by applications from healthcare (kidney exchange), social interactions (online dating, job market), and telecom/internet (sponsored search auctions and online auctions, load balancing for content delivery networks, distributed caching problems, on-demand video/movie requests). Analyis of online versions of classical bipartite matching problems, as well as of other related problems such as the matroid secretary problems as well as more general linear programming problems. Include also issues associated with incentives for market participation.

2. Real-time Paths Tracking/Predictions and On-Demand Route Guidance Under Uncertainty: This overall activity is to develop novel algorithms using real-time data (from many heterogeneous sources) in order to (i) track and predict paths in dynamic transportation networks, and (ii) provide on-demand route guidance under uncertainty. Based on a combination of optimization, data-fusion, machine learning, and novel behavioral techniques. The aim is to develop rigorous data-driven algorithms and methodologies with provable properties, and practical implementations.

current funding:

Singapore MIT Research Alliance (SMART): Future Urban Mobility II (2016-21)

Office of Naval Research (ONR): Online Optimization and Learning under Uncertainty (2015-18)

Office of Naval Research (ONR): Decentralized Online Optimization in Multi-Agent Systems in Dynamic and Uncertain Environments (2012-17)

[ Home | General | Research | Teaching ]
Last modified May 2016.