Tom Schaul
Scholar

Tom Schaul

Google Scholar ID: vDimc-4AAAAJ
Senior Staff Scientist, DeepMind
Reinforcement LearningDeep LearningDeep Reinforcement LearningGame AIExploration
Citations & Impact
All-time
Citations
34,885
 
H-index
43
 
i10-index
72
 
Publications
20
 
Co-authors
126
list available
Resume (English only)
Academic Achievements
  • - Published papers in top conferences and journals such as NeurIPS 2022, Nature Communications 2020, Nature 2019
  • - Served various roles in international conferences like program chair for RLC 2026, area chair for ICML 2024
  • - Involved in significant projects including StarCraft II
Research Experience
  • - Postdoc at the Courant Institute of NYU, in Yann LeCun's lab, 2011-2013
  • - Senior Staff Research Scientist at DeepMind London, current position
Education
  • - MSc from EPFL (Switzerland), 2005
  • - PhD from TU Munich, supervised by Jürgen Schmidhuber at IDSIA, 2011
Background
  • - Research Interests: (modular/hierarchical) reinforcement learning, (stochastic/black-box) optimization with minimal hyperparameter tuning, and (deep/recurrent) neural networks.
  • - Favorite Application Domain: Games
  • - Grew up in Luxembourg
Miscellany
  • - Has a particular interest in games