• Graduate Program
  • Research
  • Browse our Courses
  • Events
    • Events Calendar
    • Events Archive
    • Tinbergen Institute Lectures
    • Summer School
      • Deep Learning
      • Economics of Blockchain and Digital Currencies
      • Foundations of Machine Learning with Applications in Python
      • Marketing Research with Purpose
      • Modern Toolbox for Spatial and Functional Data
      • Sustainable Finance
      • Tuition Fees and Payment
      • Tinbergen Institute Summer School Program
    • Annual Tinbergen Institute Conference archive
  • News
  • Summer School
    • Deep Learning
    • Economics of Blockchain and Digital Currencies
    • Foundations of Machine Learning with Applications in Python
    • Marketing Research with Purpose
    • Modern Toolbox for Spatial and Functional Data
    • Sustainable Finance
  • Alumni
Home | People | Jannis Kurtz
 placeholder

Jannis Kurtz

Research Fellow

University
University of Amsterdam
Research field
Operations Analytics
Interests
Mathematical Methods, Operations Research, Machine Learning

Biography

Jannis Kurtz is Assistant Professor at the Business School of the University of Amsterdam. He received his PhD from the Department of Mathematics at TU Dortmund University and was later affiliated as a Postdoc to the RWTH Aachen University. His research interests are located at the intersection of robust optimization, machine learning and explainability where some of his works were published in Mathematical Programming, SIAM Journal on Optimization and at NeurIPS/ICLR. Since 2022 he is co-organizer of the Robust Optimization Webinar.

Publications

Kurtz, J., Birbil, Ş.İlker and den Hertog, D. (2026). Counterfactual explanations for linear optimization European Journal of Operational Research, 329(1):24--41.

Maragno, D., Kurtz, J., Röber, T., Goedhart, R., Birbil, Ş. and den Hertog, D. (2024). Finding regions of counterfactual explanations via robust optimization INFORMS Journal on Computing, 36(5):1316–1334.

Chassein, A., Goerigk, M., Kurtz, J. and Poss, M. (2019). Faster algorithms for min-max-min robustness for combinatorial problems with budgeted uncertainty European Journal of Operational Research, 279(2):308--319.