Past Talks

January 29, 2021:

• Merve Bodur (University of Toronto), Inverse Mixed Integer Optimization: Polyhedral Insights and Trust Region Methods

• Ward Romeijnders (University of Groningen), A Converging Benders’ Decomposition Algorithm for Two-Stage Mixed-Integer Recourse Models

December 4, 2020:

• Alfredo Torrico (Polytechnique Montréal), The Greedy Algorithm: An Effective and Flexible Tool in Submodular Optimization

• Cheng Guo (University of Toronto), Copositive Duality for Discrete Markets and Games

• David Bernal (Carnegie Mellon University), Modern Computational Approaches to Nonlinear Discrete Optimization and their Application to Process Systems Engineering

October 23, 2020:

• Felipe Serrano (Zuse Institute Berlin), Monoidal Strengthening

• Santanu Dey (Georgia Tech), Sparse PSD Approximation of the PSD Cone

October 2, 2020:

• Tuomas Sandholm (Carnegie Mellon University), Configuring Algorithms Automatically: From Practice to Theory

• Andrea Lodi (Polytechnique Montréal), Fair COVID-19 Test Allocation at Roche

July 14, 2020:

• Jannis Kurtz (University of Siegen), Discrete Optimization Methods for Group Model Selection in Compressed Sensing

July 7, 2020:

• Amitabh Basu (Johns Hopkins University), Provable complexity bounds for integer programming algorithms

• Aida Khajavirad (Rutgers University), The ratio-cut polytope and K-means clustering

June 30, 2020:

• Timo Berthold (FICO), Learning to Scale

• Jean Pauphilet (London Business School), A Unified Approach to Mixed-Integer Optimization: Nonlinear Formulations and Scalable Algorithms

June 23, 2020:

• Ricardo Fukasawa (University of Waterloo), Enforcing non-anticipativity in a two-stage stochastic program for scheduling with endogenous uncertainties

• Austin Buchanan (Oklahoma State University), Imposing contiguity constraints in political districting models

June 16, 2020:

• Axel Parmentier (Ecole des Ponts ParisTech), Learning to approximate industrial problems by operations research classic problems

• Dolores Romero Morales (Copenhagen Business School), On Enhancing the Interpretability of Data Science Models via Dimensionality Reduction

June 2, 2020:

• Weijun Xie (Virginia Tech), Best Submatrix Selection: Strong Formulations and Approximation Algorithms

• Andrés Gómez (USC), Outlier detection in time series via mixed-integer conic quadratic optimization

May 26, 2020:

• Hadi Charkhgard (USF), The Magic of Nash Social Welfare in Optimization: Do Not Sum, Just Multiply!

• Phebe Vayanos (USC), Active Preference Elicitation via Adjustable Robust Optimization

May 12, 2020:

• Simge Kuçukyavuz (Northwestern), Distributionally Robust Chance-Constrained Programs with Right-Hand Side Uncertainty under Wasserstein Ambiguity

• Hussein Hazimeh (MIT), Sparse Regression at Scale: Branch-and-Bound rooted in First-Order Optimization

May 5, 2020:

• Beste Basciftci (Georgia Tech), Adaptive Two-Stage Stochastic Programming with an Application to Capacity Expansion Planning

• Margarita Castro (University of Toronto), A Combinatorial Cut-and-Lift Procedure with an Application to 0-1 Chance Constraints

April 28, 2020:

• Sriram Sankaranarayanan (Polytechnique Montreal), When Nash Meets Stackelberg

• Siqian Shen (University of Michigan), New Results and Applications of Facility Location involving Competition, Prioritization, or Decision-dependent Demand

April 21, 2020:

• Hamed Rahimian (Northwestern University), A Model of Supply-Chain Decisions for Resource Sharing with an Application to Ventilator Allocation to Combat COVID-19

• Pierre Le Bodic (Monash University), Estimating the Size of the Branch and Bound Tree