Prof. Dr. Martin Bichler



Contact Details

Visitenkarte in TUMonline

Academic Career and Research Areas

Martin Bichler has contributed to different areas in computer science, operations research, and information systems. In particular, he is interested in market design and optimization, econometrics, and machine learning.  He is full professor at the Department of Computer Science of the Technical University of Munich (TUM). Professor Bichler is also affiliated with the TUM School of Management.

Prof. Bichler received his MSc degree from the Technical University of Vienna, and his Ph. D. as well as his Habilitation from the Vienna University of Economics and Business. He was a research fellow at UC Berkeley, and a research staff member at the IBM T. J. Watson Research Center, Yorktown Heights, New York. Later, he was a visiting scholar at the University of Cambridge, at HP Labs Palo Alto, at the Department of Economics at Yale University, and at the Department of Economics at Stanford University.


  • DFG Koselleck Project (2019)
  • INFORMS ISS Design Science Award (2008, 2019)
  • EURO Excellence in Practice Award (2018)
  • INFORMS Daniel H. Wagner prize (runner-up) (2018)
  • IBM Faculty Award (2008)

E. Baldwin, M. Bichler, M. Fichtl, and P. Klemperer. Walrasian equilibria in the strong-substitutes product-mix auction. Mathematical Programming, 191(2), 2022.


M. Bichler, P. Milgrom, and G. Schwarz. Taming the communication and computation complexity of combinatorial auctions: The FUEL bid language. Management Science, forthcoming, 2022.


M. Bichler, M. Fichtl, S. Heidekrüger, N. Kohring, and P. Sutterer. Learning equilibria in symmetric auction games using artificial neural networks. Nature Machine Intelligence, 3:687–695, August 2021.


M. Bichler and S. Waldherr. Core-pricing in combinatorial exchanges with financially constrained buyers: Computational hardness and algorithmic solutions. Operations Research, 69, 2021.


P. Karaenke, M. Bichler, and S. Minner. Coordination is hard: Electronic auction mechanisms for increased efficiency in transportation logistics. Management Science, 65(12):5449–5956, 2019.