Past Talks

April 26, 2024:

• Qimeng (Kim) Yu (Université de Montréal), On constrained mixed-integer DR-submodular minimization

• Madeleine Udell (Stanford University), AI and the future of optimization modeling

March 29, 2024:

• Jose Walteros (SUNY Buffalo), A branch-and-bound framework to solve a general class of interdependent multi-stage interdiction games

• David Bergman (UConn), Sports betting with discrete optimization (No video recording)

February 23, 2024:

• Bartolomeo Stellato (Princeton University), Differentiable Cutting-plane Layers for Mixed-integer Linear Optimization

• Karen Aardal (TU Delft), Machine-learning augmented branch-and-bound for mixed-integer linear optimization

January 26, 2024:

• Marleen Balvert (Tilburg University), IRELAND: Iterative Rule Extension for the Logical ANalysis of Data

December 1, 2023:

• Silvia Di Gregorio (Université Sorbonne Paris Nord), A Knowledge Compilation Take on Binary Polynomial Optimization

• Jan Kronqvist (KTH Royal Institute of Technology), Building upon linear MIP techniques to solve convex MINLP

November 3, 2023:

• Álinson Santos Xavier (Argonne National Laboratory), MIPLearn: An Extensible Framework for Learning-Enhanced Optimization

October 6, 2023:

• Selvaprabu Nadarajah (University of Illinois at Chicago), Self-Adapting Network Relaxations for Weakly Coupled Markov Decision Processes

• Maryam Daryalal (HEC Montréal), A hybrid logic-based Benders decomposition approach for the network migration problem

April 28, 2023:

• Yatharth Dubey (Carnegie Mellon University / University of Illinois at Urbana-Champaign), Theoretical and Computational Analysis of Strong Branching

• Georgina Hall (INSEAD), Traceability Technology Adoption in Supply Chain Networks

March 24, 2023:

• Marcia Fampa (Universidade Federal do Rio de Janeiro), Convex integer nonlinear programming for maximum-entropy sampling

• Emily Tucker (Clemson University), Mitigating New Threats to the Global Drug Supply: Supply Chain Design under Geopolitical Strain

February 24, 2023:

• Harsha Nagarajan (Los Alamos National Laboratory), Learning to Accelerate Partitioning-based Algorithms for the Global Optimization of Non-convex Programs

• Kevin Tierney (Universität Bielefeld), Search heuristics for solving combinatorial optimization problems with deep reinforcement learning

December 9, 2022:

• Claudio Contardo (Concordia University), MIP-based branch-and-bound for the discrete ordered median problem

• Anand Subramanian (Universidade Federal da Paraíba), Conference scheduling: a clustering-based approach

November 18, 2022:

• Joseph Paat (University of British Columbia), The column-number of a Delta-modular matrix

• Christopher Hojny (Eindhoven University of Technology), The role of rationality in integer programming relaxations

October 28, 2022:

• Anirudh Subramanyam (Penn State), Branch-price-and-cut algorithms for robust vehicle routing under uncertainty

• Sophie Huiberts (Columbia University), Integer programming column generation: Accelerating branch-and-price for set covering, packing, and partitioning problems

September 23, 2022:

• Laura Sanità (Bocconi University), On the Simplex method for 0/1 polytopes

• Elina Rönnberg (Linköping University), Integer programming column generation: Accelerating branch-and-price for set covering, packing, and partitioning problems

April 29, 2022:

• Swati Gupta (Georgia Tech), Reusing Combinatorial Structure for Projections over Submodular Polytopes

• Emma Frejinger (Université de Montréal), Fast Heuristic L-Shaped Method Through Machine Learning

March 25, 2022:

• Jorge Sefair (Arizona State University), Continuous location models in the presence of obstacles: an application to wireless sensor networks 

• Alexandra Newman (Colorado School of Mines), Optimizing Design and Operations of Concentrated Solar Power Plants

February 25, 2022:

• Danial Davarnia (Iowa State University), Rectangular decomposition of mixed integer programs via decision diagrams with application to unit commitment

• Michaël Poss (LIRMM), Optimization problems in graphs with locational uncertainty

January 28, 2022:

• Marc Pfetsch (TU Darmstadt), Presolving for Mixed-Integer Semidefinite Optimization

• Victor Zavala (University of Wisconsin-Madison), Solution of Large-Scale Supply Chain Models using Graph Sampling & Coarsening

December 10, 2021:

• Ivana Ljubic (ESSEC Business School of Paris), Lower Bounds for Ramsey Numbers on Circulant Graphs: A Bilevel Optimization Approach

November 19, 2021:

• Carla Michini (University of Wisconsin-Madison), The Price of Anarchy in Series-Parallel Network Congestion Games

• Christian Tjandraatmadja (Google), Constrained Discrete Black-Box Optimization using Mixed-Integer Programming

October 15, 2021:

• Yuri Faenza (Columbia), Stable matchings, lattices, and polytopes

• Margarida Carvalho (Université de Montréal), Sequential matching markets

April 30, 2021:

• Robert Hildebrand (Virginia Tech), Compact mixed-integer programming relaxations in quadratic optimization

• Ruth Misener (Imperial), Partial Lasserre Relaxation for Sparse Max Cut

March 26, 2021:

• Yiling Zhang (University of Minnesota), Building Load Control using Distributionally Robust Binary Chance-Constrained Programs with Right-Hand Side Uncertainty and the Adjustable Variants

• Andrew Trapp (Worcester Polytechnic Institute), A Comparative Study of Stability Representations for Solving Many-to-One Matching Problems with Ties and Incomplete Lists via Integer Optimization

February 26, 2021:

• Thibaut Vidal (Polytechnique Montréal), Born-Again Tree Ensembles:  Seeing the Forest for the Trees

• Marianna De Santis (Sapienza Università di Roma), Exact approaches for multiobjective mixed integer nonlinear programming problems

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