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Invited Speakers

Ton Dieker

Columbia University, Data Science Institute
Mudd 419, 500 W 120th St, New York NY 10027; USA
dieker (at symbol)

QPLEX: A next-generation methodology for stochastic network analysis (PART 1+2)

Short Bio

Ton Dieker is Associate Professor of Industrial Engineering and Operations Research at Columbia University, and a member of Columbia’s Data Science Institute. He received an M.Sc. from Vrije Universiteit Amsterdam (2002) and a Ph.D. from University of Amsterdam (2006). Prior to joining Columbia, he was the Fouts Family Associate Professor at Georgia Tech. Honors and awards include the Goldstine Fellowship from IBM Research, the Erlang Prize from the INFORMS Applied Probability Society, and a PECASE Award from the White House. He serves/has served on the editorial board of several journals in Operations Research and Applied Probability.

Andrea Lodi

École Polytechnique de Montréal
GERAD - HEC Montreal; 3000, Cote-Sainte-Catherine Rd
Montreal (Quebec) H3T 2A7; Canada
andrea.lodi 'at'

Exact Combinatorial Optimization with Graph Convolutional Neural Networks
Tactical Planning by Machine Learning

Short Bio

Andrea Lodi received the PhD in System Engineering from the University of Bologna in 2000 and he has been Herman Goldstine Fellow at the IBM Mathematical Sciences Department, NY in 2005–2006. He has been full professor of Operations Research at DEI, University of Bologna between 2007 and 2015. Since 2015 is Canada Excellence Research Chair in “Data Science for Real-time Decision Making” at the École Polytechnique de Montréal. His main research interests are in Mixed-Integer Linear and Nonlinear Programming and Data Science and his work has received several recognitions including the IBM and Google faculty awards. He is author of more than 100 publications in the top journals of the field of Mathematical Optimization and Data Science. He serves as Editor for several prestigious journals in the area. He has been network coordinator and principal investigator of two large EU projects/networks, and, since 2006, consultant of the IBM CPLEX research and development team. Finally, Andrea Lodi is the co-principal investigator of the project "Data Serving Canadians: Deep Learning and Optimization for the Knowledge Revolution", recently generously funded by the Canadian Federal Government under the Apogée Programme and scientific co-director of IVADO, the Montréal Institute for Data Valorization.

Bernhard von Stengel

London School of Economics and Political Science
Houghton Street, London, WC2A 2AE, UK

Progress and Challenges in Computing Nash Equilibria (PART 1+2)

Short Bio

Bernhard von Stengel is Professor of Mathematics at the London School of Economics which he joined in 1998, after studies in Germany and the USA. He has been communications officer of the Game Theory Society, and was program chair of the GAMES 2016 congress in Maastricht. He is interested in mathematical questions of game theory. The geometry and computation of Nash equilibria is one of his research specialities.

Virginia Vassilevska Williams

77 Massachusetts Ave., 38-401
Cambridge, MA 02139, USA

Fine-Grained Algorithms and Complexity
Limitations on All Known (and Some Unknown) Approaches to Matrix Multiplication

Short Bio

Virginia Vassilevska Williams is the Steven and Renee Finn Career Development Associate Professor at MIT CSAIL. She obtained her Ph.D. from Carnegie Mellon University in 2008. After research and postdoctoral positions at the IAS in Princeton, UC Berkeley and Stanford, she spent 3.5 years as an assistant professor at Stanford University before joining MIT in early 2017. She is the recipient of an NSF CAREER award, a Google Faculty Research Award and an Alfred P. Sloan Research Fellowship, and in 2018 gave an invited lecture at the International Congress of Mathematicians.