Our guest today is Petar Veličković, Staff Research Scientist at Google DeepMind and Affiliated Lecturer at University of Cambridge.
In our conversation, we first dive into how Petar got into Graph ML and discuss his most cited paper: Graph Attention Networks. We then dig into DeepMind where Petar shares tips and advice on how to get into this competitive company and explains the difference between research scientists and research engineering roles.
We finally talk about applied work that Petar worked on including building Google Maps' ETA algorithm and an AI coach football coach assistant to help Liverpool FC improve corner kicks.
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Graph Attention Networks Paper: https://arxiv.org/abs/1710.10903
ETA Prediction with Graph Neural Networks in Google Maps: https://arxiv.org/abs/2108.11482
TacticAI: an AI assistant for football tactics (with Liverpool FC): https://arxiv.org/abs/2402.01306
Follow Petar on LinkedIn: https://www.linkedin.com/in/petarvelickovic/
Follow Neil on LinkedIn: https://www.linkedin.com/in/leiserneil/
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(00:00) - Intro
(02:44) - How Petar got into AI
(06:14) - GraphML and Geometric Deep Learning
(10:10) - Graph Attention Networks
(17:00) - Joining DeepMind
(20:24) - What Makes DeepMind People Special?
(22:28) - Getting into DeepMind
(24:36) - Research Scientists Vs Research Engineer
(30:40) - Petar's Career Evolution at DeepMind
(35:20) - Importance of Side Projects
(38:30) - Building Google Maps ETA Algorithm
(47:30) - Tactic AI: Collaborating with Liverpool FC
(01:03:00) - Career advice