Anders Wikum

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wikum@stanford.edu

I am a third year PhD Candidate in Management Science & Engineering at Stanford University, advised by Ellen Vitercik. My research focuses on the design of machine learning-based algorithms for discrete optimization and is supported by a 2022 National Defense Science & Engineering Graduate (NDSEG) fellowship.

Prior to Stanford, I earned a B.S. in Operations Research from Cornell University in 2021 before spending a year in Boston as a consultant/data scientist at QuantumBlack.

selected publications

  1. ICML
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    Algorithms with Calibrated Machine Learning Predictions
    Judy Hanwen Shen, Ellen Vitercik, and Anders Wikum
    In International Conference on Machine Learning (ICML), 2025
    Spotlight arXiv
  2. CPAIOR
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    LLMs for Cold-Start Cutting Plane Separator Configuration
    Connor Lawless, Yingxi Li, Anders Wikum, Madeleine Udell, and Ellen Vitercik
    In International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR), 2024
    arXiv
  3. ICML
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    MAGNOLIA: Matching Algorithms via GNNs for Online Value-to-go Approximation
    Alexandre Hayderi, Amin Saberi, Ellen Vitercik, and Anders Wikum
    In International Conference on Machine Learning (ICML), 2024
    arXiv