This is the list in the Tutorials track, co-chaired by Dionne Aleman and myself.
All tutorials are in Room 108A – CC
SA (8am) Data-driven stochastic programming using Phi-divergences, Guzin Bayraksan, Ohio State University
SB (11am) Pricing inspired by data and practice, by Georgia Perakis, MIT
SC (1:30pm) Uncertainty in demand response – identification, estimation and learning by Josh Taylor and Johanna Mathieu, U.Toronto
SD (4:30pm) Robust optimization and risk ambiguity by Erick Delage, HEC Canada and Dan Iancu, Stanford.
MA (8am) A practical guide to ranking and selection methods by Dave Goldsman, Georgia Tech
MB (11am) Markov Decision Processes in healthcare by Andrew Schaefer, Rice University
MC (1:30pm) Equilibrium routing and its paradoxes by Asu Ozdaglar, MIT
MD (4:30pm) Computational optimization and statistical methods for big data analytics: applications in neuroimaging, Art Chaovalitwongse and Shuai Huang, UW Seattle
TA (8am) Applying machine learning in online revenue management by David Simchi-Levi, MIT
TB (11am) Approximations of queueing performance for rapid systems design by Ton Dieker, Columbia University
TC (1:30pm) Discrete optimization models for homeland security and disaster management by Laura McLay, UW Madison
TD (4:30pm) Meta-algorithms: from algorithm tuning and configuration to algorithm portfolios by Meinolf Sellmann, IBM