PeopleofSuperintelligence

Researcher

Dino Sejdinovic

Dino Sejdinovic is a statistical machine learning researcher whose kernel work includes tests for independence and multivariate interaction. He earned a mathematics and theoretical computer science degree in Sarajevo, completed an electrical and electronic engineering PhD at Bristol, and held postdoctoral posts in Bristol and London. At Oxford, he held statistics roles from Lecturer to Associate Professor and coauthored a Random Fourier Features paper that received an ICML 2019 best-paper honorable mention; he also coauthored a deep learning study of cloud perturbations caused by anthropogenic aerosol. At Adelaide University, he is a Professor of Statistical Machine Learning and co-leads a Responsible AI Research Centre theme; he is also a Visiting Professor in Tokyo and Singapore, since 2024 and 2025 respectively.

Badges

Timeline

  1. 2006–2009

    From Sarajevo to Bristol

    At the University of Sarajevo, he earns a Diplom in Mathematics and Theoretical Computer Science in 2006. He completes a PhD in Electrical and Electronic Engineering at the University of Bristol in 2009.

  2. 2009–2014

    Bristol and UCL postdoctoral research

    He holds a postdoctoral position at the Institute for Statistical Science, University of Bristol, from 2009 to 2011, then one at University College London's Gatsby Computational Neuroscience Unit from 2011 to 2014.

  3. 2013

    Kernel tests for interaction

    In 2013, he coauthors A Kernel Test for Three-Variable Interactions, which introduces kernel nonparametric tests for Lancaster interaction and total independence through embeddings in a reproducing kernel Hilbert space.

  4. 2014–2022

    Statistics roles at Oxford

    He is a Lecturer from 2014 to 2016 and an Associate Professor in Oxford's Department of Statistics from 2016 to 2022. He is also a Fellow of Mansfield College and a Turing Fellow.

  5. 2019

    An ICML best-paper honorable mention

    In 2019, he coauthors Towards A Unified Analysis of Random Fourier Features with Zhu Li, Jean-Francois Ton and Dino Oglic. The paper receives an honorable mention in ICML's best-paper awards.

  6. 2019

    Deep learning for cloud effects

    In 2019, he coauthors Detecting anthropogenic cloud perturbations with deep learning, which uses deep convolutional neural networks to find two cloud perturbations linked to anthropogenic aerosol and assess their properties and prevalence.

  7. Since 2022

    Professor in Adelaide

    In 2022, he moves to Adelaide as Professor in the School of Mathematical Sciences. He co-leads a theme at the Australian Institute for Machine Learning's Responsible AI Research Centre and serves on the Adelaide Data Science Centre steering committee.

  8. Since 2024

    Visiting professorships in Tokyo and Singapore

    Since 2024, he is a Visiting Professor at the Research Center for Statistical Machine Learning, The Institute of Statistical Mathematics, Tokyo. Since 2025, he is a Visiting Professor with Nanyang Technological University's College of Computing and Data Science in Singapore.

Career

  1. Since 2025Nanyang Technological UniversityVisiting Professor
  2. Since 2024Research Organization of Information and SystemsVisiting Professor
  3. Since 2022Adelaide UniversityProfessor of Statistical Machine Learning
  4. Since 2022Australian Institute for Machine LearningTheme Co-lead
  5. Since 2022Adelaide Data Science CentreSteering Committee Member
  6. 2014–2022University of OxfordLecturer, Associate Professor
  7. 2011–2014University College LondonPostdoctoral Researcher
  8. 2009–2011University of BristolPostdoctoral Researcher

Education

  1. 2009University of BristolPhD
  2. 2006University of SarajevoDiplom in Mathematics and Theoretical Computer Science

From the biography.

  1. The United States employs an estimated 48% of people shaping AIIncludes University of Adelaide. We estimate where the people shaping AI work today, how universities, companies and research institutes split across countries, and how country shares have changed since the 1960s.
  2. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes Nanyang Technological University. 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.
  3. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes Nanyang Technological University. 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.
  4. Google has the highest combined h-index among AI organizationsIncludes Nanyang Technological University. We estimate that Google holds the highest combined h-index at 8,016, while universities account for 73% of the deduplicated total across AI organizations.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

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  1. Prof Dino Sejdinovic | Researcher Profiles | Adelaide University researchers.adelaide.edu.au. Checked 21 October 2026.
  2. OxCSML : People : Dino Sejdinovic csml.stats.ox.ac.uk. Checked 21 October 2026.
  3. Two papers by OxCSML members receive ICML 2019 Best Paper Honorable Mentions csml.stats.ox.ac.uk. Checked 21 October 2026.
  4. Detecting anthropogenic cloud perturbations with deep learning arxiv.org. Checked 21 October 2026.
  5. Dino Sejdinovic sejdino.github.io. Checked 21 October 2026.