Program

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Schedule of Events

Presentations 
  • Can Deep Reinforcement Learning Improve Inventory Management? Performance on Dual Sourcing, Lost Sales and Multi-Echelon Problems. 
    Joren Gijsbrechts, Universidade Católica Portuguesa, Portugal

  • Opportunities for Ethical ML and Supply Chains
    Swati Gupta, Georgia Tech

  • Heuristics for Mixed-Integer Optimization Through a Machine Learning Lens
    Andrea Lodi
    , Cornell Tech, USA

  • How to Make Sure Machine Learning Has an Impact on Supply Chains.
    Polly Mitchell-GuthrieKinaxis

  • From Small to Large Data – How Can We Leverage Synthetic Data for ML In Operations & Supply Chain Management.
    Richard Pibernik
    , Julius-Maximilians-University, Würzburg, Germany

  • Almost Matching Exactly for Observational Causal Inference.
    Cynthia Rudin
    , Duke University, USA

  • A Practical End-to-End Inventory Management Model with Deep Learning.
    Zuo-Jun Max Shen
    , UC-Berkeley, USA / Univ. of Hong Kong

  • Algorithmic Tools for US Congressional Districting: Fairness via Analytics
    David B. Shmoys
    , Cornell University, NY, USA

  • Chips and Beer: Using Machine Learning to Optimize Inventory
    Larry Snyder, Lehigh University

  • Predicting Human Discretion to Adjust Algorithmic Prescription: A Large-Scale Field Experiment In Warehouse Operations.
    Jiankun Sun
    , Imperial College London, UK

  • Data-driven Stochastic Vehicle Routing Problem and Job Shop Using Reinforcement Learning 
    Martin Takáč, Lehigh University, Bethlehem, USA

  • Same-Day Delivery with Fair Customer Service
    Barrett Thomas
    , University of Iowa, USA

  • AI/ML Applications for Industry: The Proven and Future Direction
    Michael Watson
    Coupa Software

* Please note: subject to change due to ongoing uncertainities on travel restrictions/guidelines within the USA and internationally due to COVID.