Researcher

Petar Veličković

Also known as Petar Velickovic

Petar Veličković is a research scientist whose graph-learning work includes Graph Attention Networks and Deep Graph Infomax. He studied mathematics in Belgrade and computer science at Cambridge, where he completed a PhD under Pietro Liò before joining Google DeepMind in 2019. His work on neural algorithmic reasoning explores how neural networks can execute algorithmic computation. He is a Senior Staff Research Scientist at Google DeepMind and an Affiliated Lecturer at Cambridge.

Works
120
Badges

Publication numbers from OpenAlex, as of 22 October 2026. Citations and h-index are hidden because this OpenAlex record may be incomplete or mix in other authors.

Timeline

  1. 2008–2015

    From Belgrade to Cambridge

    At Matematička gimnazija in Belgrade, he studies specialised mathematics, physics and computer science through 2012. He earns first-class honours in computer science at Trinity College, Cambridge, in 2015.

  2. 2016–2019

    A Cambridge PhD

    From 2016 to 2019, he works as a research assistant in Cambridge's Artificial Intelligence Group and completes a computer science PhD under Pietro Liò. In 2016, he is a research associate at Nokia Bell Labs; he visits Mila for graph-learning research in 2017 and 2018.

  3. 2017–2018

    Graph attention and Deep Graph Infomax

    In 2017, he coauthors Graph Attention Networks, which introduces masked self-attention for graph data. In 2018, he coauthors Deep Graph Infomax, an unsupervised method for learning node representations from graph data.

  4. 2019–2021

    Research scientist at DeepMind

    He joins Google DeepMind in 2019 as a Research Scientist, becomes a Senior Research Scientist in 2020, and becomes a Staff Research Scientist in 2021.

  5. 2021

    Neural algorithmic reasoning

    In 2021, he coauthors a paper that frames neural algorithmic reasoning as neural networks able to execute algorithmic computation.

  6. 2024

    Paper of the Year runner-up

    In 2024, he is named runner-up for Current Opinion in Structural Biology's 2023 Paper of the Year for “Everything is Connected: Graph Neural Networks.”

  7. Since 2021

    Teaching at Cambridge

    Since 2021, he holds an Affiliated Lectureship in Cambridge's Department of Computer Science and Technology and is an Associate of Clare Hall. He co-teaches the Geometric Deep Learning MPhil course with Pietro Liò.

  8. As of October 2026

    Senior Staff at DeepMind

    He is a Senior Staff Research Scientist at Google DeepMind. His research focuses on neural architectures for graph data, algorithmic reasoning and computational biology.

Career

  1. Since 2019Google DeepMindResearch Scientist, Senior Research Scientist
  2. Since 2016University of CambridgeResearch Assistant, Affiliated Lecturer
  3. 2017–2018Mila
  4. 2016Bell LabsResearch Associate

Education

  1. 2019University of CambridgePhD
  2. 2015Trinity College, University of Cambridge

Sources and credits

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  1. Experience | Petar Veličković petar-v.com. Checked 20 October 2026.
  2. Petar Velickovic | Department of Computer Science and Technology cst.cam.ac.uk. Checked 20 October 2026.
  3. Petar Veličković research.google. Checked 20 October 2026.
  4. Graph Attention Networks arxiv.org. Checked 20 October 2026.
  5. Deep Graph Infomax arxiv.org. Checked 20 October 2026.
  6. Neural Algorithmic Reasoning arxiv.org. Checked 20 October 2026.