Søren Riis

Reader in Computer Science · Queen Mary University of London

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  • Affiliation: School of EECS, QMUL (Centre for Fundamentals of AI and Computational Theory)
  • Email: s.riis@qmul.ac.uk
  • Address: Mile End Road, London E1 4NS, United Kingdom
  • Web: Personal webpage

Research

My research spans logic and proof complexity, information theory and network coding, and algorithmic/combinatorial methods. In recent work I also study reinforcement learning and representation/learnability barriers in games.

Employment

Queen Mary University of London
Reader in Computer Science (2000–present)
Fetch.AI (Cambridge)
Industry consultancy (part-time, 2018–2019)

Earlier academic positions and research visits include (selected): LBRICS (Aarhus), University of Leeds, Hebrew University of Jerusalem, University of Lund, and Ohio State University.

Education

University of Oxford
DPhil in Mathematics (Mathematical Logic), 1994
University of Copenhagen
MSc in Mathematics and Physics, 1989

Fellowships, service & academic activity

Fellowships & leadership

  • Research fellowships: The Fields Institute (Toronto), Isaac Newton Institute (Cambridge), Institut Henri Poincaré (Paris).
  • Former research fellow / visitor at institutes and universities including the Isaac Newton Institute, the Fields Institute, and others.
  • Director and co-founder, Centre for Discrete Mathematics (QMUL).

Reviewing & community service

  • EPSRC College of Peer Reviewers (member since 2010); served on grant-review panels (UK and international).
  • Refereeing for journals and conferences in logic, complexity, information theory, combinatorics, and theoretical computer science (50+ reports).
  • External examining and assessment roles (PhD and project examination).

Teaching & supervision

  • 15+ years teaching experience across undergraduate and postgraduate levels (3,000+ students taught in total).
  • Module organisation for large cohorts; supervision and mentoring of student projects over many years.
  • Research staff / supervision in the EPSRC CDT in Intelligent Games and Game Intelligence (IGGI).

Industry & applied work

  • Consultancy: Fetch.AI (Cambridge), work on governance / hard-fork models and distributed-ledger mechanisms.
  • Applied machine-learning projects (e.g. game AI / reinforcement learning) alongside theoretical work.

Funding (selected)

  • EPSRC grant EP/H016015/1 (flows and bottlenecks) — £414,367.
  • Project leadership on funded research totalling £400k+ (research assistants and PhD students).

PhD supervision (selected)

  • Stefan Dantchev (now academic; Durham).
  • Sun Yun (now in industry; Deutsche Bank).
  • Bei Zhou (reinforcement learning and game AI).

Publications

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    Talks (recent)

    • Coin racing and waiting-time paradoxes: why fair coins are exceptional (DIMAP Seminar, University of Warwick, 26 Jan 2026)

    Awards (selected)

    • Prize winner (USD 5,000), Humanity’s Last Exam (Outlier), 2025.