PeopleofSuperintelligence

Researcher

Vladimir Vovk

Vladimir Vovk is a computer science researcher whose work on conformal prediction helps machine-learning systems communicate the reliability of their predictions. He earned a PhD at Moscow State University in 1988, held a Stanford fellowship in 1995–1996, and published work on prediction in 1998 and probability in 2001. His 2005 book and 2008 tutorial explained how conformal prediction gives confidence information for machine-learning predictions. With Ruodu Wang, he developed e-value methods for hypothesis testing; their 2021 paper received the 2026 Frontiers of Science Award. As of October 2026, he is a Professor of Computer Science at Royal Holloway, University of London.

Born
1960

Years link to their sources.

Timeline

  1. 1988

    A Moscow State University PhD

    He earns a PhD at Moscow State University in 1988 for a thesis on predicting algorithmically random sequences. Andrei Kolmogorov and Alexey Semenov supervise his thesis.

  2. 1995–1996

    A Stanford fellowship

    He holds a mathematics and statistics fellowship at Stanford's Center for Advanced Study in the Behavioral Sciences in 1995–1996.

  3. 1998

    Learning by transduction

    With Alex Gammerman and Vladimir Vapnik, he coauthors “Learning by transduction” in 1998.

  4. 2001

    Probability and finance

    He coauthors Probability and finance: it's only a game with Glenn Shafer in 2001.

  5. 2005–2008

    A conformal prediction book

    In 2005, he coauthors Algorithmic Learning in a Random World with Alex Gammerman and Glenn Shafer; the book centers on conformal prediction, a machine-learning method. In 2008, he and Glenn Shafer publish a JMLR tutorial that explains how past examples set confidence levels for new predictions.

  6. 2021

    E-values for hypothesis tests

    With Ruodu Wang, he publishes “E-values: Calibration, combination, and applications” in 2021. The paper shows that e-values can be merged simply by averaging when testing a single hypothesis, and develops efficient procedures for testing multiple hypotheses.

  7. 2026

    A Frontiers of Science Award

    He shares the 2026 Frontiers of Science Award with Ruodu Wang for their 2021 paper on e-values.

  8. As of October 2026

    Professor at Royal Holloway

    As of October 2026, he is Professor of Computer Science at Royal Holloway, University of London, with affiliations in the Centre for Machine Learning, Centre for Intelligent Systems, Centre for Reliable Machine Learning and Centre for Robust Inference in a Digital Economy (RIDE). His 2026 paper shows that conformal predictors are universal, with only limited possible gains in predictive efficiency.

Career

  1. NowRoyal Holloway University of LondonProfessor of Computer Science

Education

  1. 1988Lomonosov Moscow State UniversityPhD

From the biography.

  1. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes Royal Holloway University of London. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  2. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes Royal Holloway University of London. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  3. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Royal Holloway University of London. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  4. Google had the most people shaping AI every year from 2014 to 2025Our estimates of which organizations employed the most people shaping AI each year from 1955 to 2025, tracing the shift from university labs to companies.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

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  1. Predictability of algorithmically random sequences pure.royalholloway.ac.uk. Checked 20 October 2026.
  2. Vladimir Vovk | Center for Advanced Study in the Behavioral Sciences casbs.stanford.edu. Checked 20 October 2026.
  3. Learning by transduction - Royal Holloway Research Portal pure.royalholloway.ac.uk. Checked 20 October 2026.
  4. Probability and Finance: It's Only a Game! pure.royalholloway.ac.uk. Checked 20 October 2026.
  5. Algorithmic learning in a random world alrw.net. Checked 20 October 2026.
  6. A Tutorial on Conformal Prediction jmlr.csail.mit.edu. Checked 20 October 2026.
  7. E-values: Calibration, combination, and applications pure.royalholloway.ac.uk. Checked 20 October 2026.
  8. Professor Ruodu Wang honoured with 2026 Frontiers of Science Award uwaterloo.ca. Checked 20 October 2026.
  9. Vladimir Vovk - Royal Holloway Research Portal pure.royalholloway.ac.uk. Checked 20 October 2026.
  10. Universality of conformal prediction under the assumption of randomness proceedings.mlr.press. Checked 20 October 2026.