Loic Matthey Loic Matthey Loic Matthey

Loïc Matthey

Phd candidate at the Gatsby Computational Neuroscience Unit

I am currently doing my PhD at the Gatsby Unit, at UCL in London, under
the supervision of Peter Dayan.
My interests are broadly tuned towards neural processing leading to memory, network dynamics and temporal computations. Currently, I am studying visual short-term memory and building probabilistic models of information storage and recall.


Peer-reviewed papers

  • A Probabilistic Palimpsest Model of Visual Short-term Memory
  • Loic Matthey, Paul M Bays and Peter Dayan.
    PLoS Computational Biology, 2015, 11(1): e1004003. doi:10.1371/journal.pcbi.100400

Conference presentations

  • Probabilistic palimpsest memory: multiplicity, binding and coverage in visual short-term memory
  • Loic Matthey, Paul Bays and Peter Dayan.
    Computational and Systems Neuroscience Meeting (CoSyNe) 2012

  • Reservoir dynamics: Feedback and chaos in the network solution of a complex cognitive task
  • Loic Matthey and Peter Dayan.
    Computational and Systems Neuroscience Meeting (CoSyNe) 2011

Previous work

  • Aggregation-mediated Collective Perception and Action in a Group of Miniature Robots
    G. Mermoud, L. Matthey, W. C. Evans, and A. Martinoli
    AAMAS 2010, link
  • Stochastic Strategies for a Swarm Robotic Assembly System
    L. Matthey, S. Berman, and V. Kumar.
    ICRA 2009, doi
  • Experimental study of limit cycle and chaotic controllers for the locomotion of centipede robots
    L. Matthey, L Righetti and A J Ijspeert
    IROS 2008, doi
  • A Comparison of Casting and Spiraling Algorithms for Odor Source Localization in Laminar Flow
    T. Lochmatter, X. Raemy, L. Matthey, S. Indra, and A. Martinoli
    ICRA 2008, doi

Book chapters

  • Self-Organized Robotic Systems: Large-Scale Experiments in Aggregation and Self-Assembly using Miniature Robots
    G. Mermoud, A. Prorok, L. Matthey, C. M. Cianci, N. Correll, and A. Martinoli
    Handbook of Collective Robotics, Pan Stanford 2011, to appear.


  • Hybrid Reactions Modeling for Top-down Design Framework
    Master Thesis
    University of Pennsylvania (PENN) and EPFL.
Education and awards

PhD in Computational Neuroscience 2009 - present

Gatsby Unit, University College London

MSc in Computer Science 2006 - 2008

Ecole Polytechnique Federale de Lausanne (EPFL).
Biocomputing specialization

BSc in Computer Science 2003 - 2006

Ecole Polytechnique Federale de Lausanne (EPFL).


  • Master Level Excellency Scholarship, EPFL, 2006-2008.
  • Société Suisse d'Informatique Prize: Second best Grade Point Average of Master, including the Master Thesis (obtained GPA: 5.87 / 6.0), 2008.
  • Foundation Annaheim Prize: Rewards a high-quality Master Thesis bringing life science and computer science closer together.

Theoretical Neuroscience, Gatsby Unit, 2010

Probabilistic and Unsupervised Learning, Gatsby Unit 2010

Introduction to Scientific Programming in Python, UCL Graduate School 2012, 2013

Software and others

Github for Bayesian Visual Working Memory

Curriculum vitae