Department of Informatics – Computation and Economics Research Group

 

Timo Mennle

Timo Mennle
Timo Mennle
Ph.D. Student
Department of Informatics
University of Zurich
Binzmühlestrasse 14
CH-8050 Zürich
Room BIN 2.A.13
Tel +41 44 635 43 32
Email mennle@ifi.uzh.ch

Short Bio

Since January 2012, Timo is a Ph.D. student in the Computation and Economics Research Group at the Department of Informatics of the University of Zurich. In 2009, he received a MSc (Diplom) in Mathematics with a minor in Computer Science from the University of Freiburg, Germany. From January 2010 till December 2011, Timo worked as a management consultant for the Business Technology Office of McKinsey & Company.

Research Interests

Matching Markets; Assignment Mechanisms; Prediction Markets; Financial Markets; Pricing Mechanisms; Mechanism Design; Electronic Commerce.

Research Papers

  • The Power of Local Manipulation Strategies in Assignment Mechanisms.
    Timo Mennle, Michael Weiss, Basil Philipp, and Sven Seuken. In Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI), Buenos Aires, Argentina, August 2015.[pdf]
  • The Efficient Frontier in Randomized Social Choice.
    Timo Mennle and Sven Seuken. March 2015.[pdf]
  • The Naive versus the Adaptive Boston Mechanism.
    Timo Mennle and Sven Seuken. June 2014.[pdf]
  • An Axiomatic Approach to Characterizing and Relaxing Strategyproofness of One-sided Matching Mechanisms.
    Timo Mennle and Sven Seuken. Extended Abstract in Proceedings of the 15th ACM Conference on Economics and Computation (EC), Palo Alto, USA, June 2014.[pdf (full paper)]
  • Hybrid Mechanisms: Trading off Strategyproofness and Efficiency in One-Sided Matching.
    Timo Mennle and Sven Seuken. Working paper. February 2014.[pdf]

Other Articles

  • An Axiomatic Characterization of Strategyproof Ordinal Mechanisms with Indifferences.
    Timo Mennle and Sven Seuken. Research Note. July 2014.[pdf]
  • Relaxing Strategyproofness in One-sided Matching.
    Timo Mennle and Sven Seuken. ACM SIGecom Exchanges, Vol. 13, No. 1, June 2014.[pdf]

Teaching

Advised Theses (with Sven Seuken)

  • Leveraging Competition Amongst Peers as a Motivating Factor in Learning Software.
    Bachelor Thesis by Stefan Bublitz. 2014.
  • Matching Experiments on Amazon Mechanical Turk.
    Bachelor Thesis by Michael Weiss. 2014.
  • Simulation of Boundedly Rational Manipulation Strategies in One-Sided Matching Markets.
    Bachelor Thesis by Basil Philipp. 2013.
  • Analysing Prediction Markets.
    Independent Study by Leonardo Stedile. 2013.