Vladimir Vovk

{{Short description|British computer scientist}}

{{Use dmy dates|date=April 2022}}

{{BLP sources|date=February 2022}}

{{infobox scientist/Wikidata|suppressfields=doctoral_students

| fetchwikidata=ALL

| birth_place = Ukraine

| nationality = British

| known_for = Conformal prediction

| fields = Machine learning
Statistics

}}

Vladimir Vovk is a British computer scientist, and professor at Royal Holloway University of London. He is the co-inventor of Conformal prediction and is known for his contributions to the concept of E-values. He is the co-director of the Centre for Machine Learning at Royal Holloway University of London, and a Fellow of the Royal Statistical Society.

Career

Vovk started working as a researcher in the Russian Academy of Sciences, then became a Fellow in the Center for Advanced Study in the Behavioral Sciences at Stanford University.{{cite web|url=https://casbs.stanford.edu/people/vladimir-vovk|title=Stanford University's Fellow |year=2021 |publisher=Stanford University, USA|accessdate={{Format date|2021|12|11}}}} He was appointed as a professor of Computer Science at Royal Holloway and Bedford New College, where he currently serves as co-director of the Centre for Machine Learning.

Early in his career, Vovk was heavily involved in the development of the foundations of probability, along with Glenn Shafer. Their work has resulted in a book, Probability and Finance: It's Only a Game!, published in 2001, which was subsequently translated into Japanese in 2006 by Masayuki Kumon and edited by Kei Takeuchi. In 2005, he co-invented the Conformal prediction framework with Alexander Gammerman.

Vovk has delivered speeches all around the world. In 2021, he was invited to deliver a series of memorial lectures to Prasanta Chandra Mahalanobis in India.{{cite web|url=https://www.isibang.ac.in/~statmath/pcm2020/|title=P.C. Mahalanobis Memorial Lectures 2020-21 |year=2021 |publisher=Indian Statistical Institute, Kolkata|accessdate={{Format date|2021|11|17}}}} On the 20-year anniversary of The Society for Imprecise Probability (SIPTA) in 2019, he was invited to deliver a talk on "Game-theoretic foundations for imprecise probabilities" in Belgium.{{cite web|url=https://www.sipta.org/isipta19/invited-speakers/|title=SIPTA 2019 invited speakers |year=2019 |publisher=The Society for Imprecise Probability|accessdate={{Format date|2021|11|18}}}} In 2016, he delivered a seminar about "Probability-free theory of continuous martingales" at Imperial College in the UK.{{cite web|url=https://www.imperial.ac.uk/events/101678/vladimir-vovk-basics-of-a-probability-free-theory-of-continuous-martingales/|title=Imperial College UK seminar 2016 |year=2016 |publisher=Imperial College, UK|accessdate={{Format date|2021|12|11}}}} In 2014, he delivered a seminar at University of Hawai'i in the USA.{{cite web|url=https://www.ics.hawaii.edu/2015/01/seminar-vladimir-vovk-university-of-london-game-theoretic-probability-a-brief-review/|title=University of Hawai'i seminar 2014 |year=2014 |publisher=University of Hawai'i, USA|accessdate={{Format date|2021|12|11}}}}

Vovk has written 9 books, more than 280 research papers, and has an estimated h-index of 53.{{cite web|url=https://scholar.google.com/citations?user=GJE29ekAAAAJ|title=Vovk's Google Scholar Page |year=2021 |publisher=Google Scholar|accessdate={{Format date|2022|4|9}}}} He holds fellowship positions at Stanford University (USA), Arizona State University (USA) and Yandex (Russia).{{cite web|url=https://cubic.asu.edu/content/vladimir-vovk|title=Arizona State University's Fellow |year=2021 |publisher=Arizona State University, USA|accessdate={{Format date|2021|12|11}}}}{{cite web|url=https://research.yandex.com/people/603774|title=Yandex Researcher |year=2021 |publisher=Yandex, Russia|accessdate={{Format date|2021|12|11}}}}

Vovk ceased cooperation with Russian organizations in protest against Russia's invasion of Ukraine.

Selected books

  • Game-theoretic foundations for probability and finance (2019), Wiley, {{ISBN|0470903058}}.
  • Conformal Prediction for Reliable Machine Learning: Theory, Adaptations and Applications (2014), Morgan Kaufmann, {{ISBN|0123985374}}.
  • Algorithmic Learning in a Random World (2005), Springer, {{ISBN|0387001522}}.
  • Probability and finance: it's only a game (2001), Wiley, {{ISBN|0471402265}}.

References

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