2026 Timothy P. Lillicrap: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	64	2504	2426	142	140	129	86663

Overview

Timothy P. Lillicrap is affiliated with University College London in the United Kingdom and specializes primarily in the field of Computer Science. They have contributed extensively to research areas including Artificial Intelligence, Cognitive Neuroscience, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, and Control and Systems Engineering.

Their research predominantly focuses on key topics such as Reinforcement Learning in Robotics, Neural dynamics and brain function, Multimodal Machine Learning Applications, Advanced Memory and Neural Computing, Robot Manipulation and Learning, Topic Modeling, and Natural Language Processing Techniques.

Timothy Lillicrap has published in multiple venues, with a noticeable presence in both preprint and peer-reviewed outlets. The frequent publication venues include arXiv (Cornell University), bioRxiv (Cold Spring Harbor Laboratory), Nature reviews. Neuroscience, Nature Communications, and Software Impacts.

Backpropagation and the brain, 2020, Nature reviews. Neuroscience
Gemini: A Family of Highly Capable Multimodal Models, 2023, arXiv (Cornell University)
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context, 2024, arXiv (Cornell University)
Catalyzing next-generation Artificial Intelligence through NeuroAI, 2023, Nature Communications
dm_control: Software and tasks for continuous control, 2020, Software Impacts

Their collaborations include frequent co-authorship with a team of researchers who have contributed to multiple publications together. Notable frequent co-authors are Adam Santoro, Alistair Muldal, Blake A. Richards, Petko Georgiev, and Peter C. Humphreys.

Best Publications

Mastering the game of Go with deep neural networks and tree search

David Silver;Aja Huang;Christopher J. Maddison;Arthur Guez

17878
Citations
Continuous control with deep reinforcement learning

Timothy P. Lillicrap;Jonathan J. Hunt;Alexander Pritzel;Nicolas Heess

11589
Citations
Mastering the game of Go without human knowledge

David Silver;Julian Schrittwieser;Karen Simonyan;Ioannis Antonoglou

10445
Citations
Asynchronous methods for deep reinforcement learning

Volodymyr Mnih;Adrià Puigdomènech Badia;Mehdi Mirza;Alex Graves

7139
Citations
Matching networks for one shot learning

Oriol Vinyals;Charles Blundell;Timothy Lillicrap;Koray Kavukcuoglu

5218
Citations
A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play.

David Silver;Thomas Hubert;Julian Schrittwieser;Ioannis Antonoglou

3933
Citations
Grandmaster level in StarCraft II using multi-agent reinforcement learning.

Oriol Vinyals;Igor Babuschkin;Wojciech M. Czarnecki;Michaël Mathieu

3527
Citations
Mastering Atari, Go, chess and shogi by planning with a learned model

Julian Schrittwieser;Ioannis Antonoglou;Thomas Hubert;Karen Simonyan

2266
Citations
Meta-learning with memory-augmented neural networks

Adam Santoro;Sergey Bartunov;Matthew Botvinick;Daan Wierstra

1640
Citations
Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates

Shixiang Gu;Ethan Holly;Timothy Lillicrap;Sergey Levine

1637
Citations
A simple neural network module for relational reasoning

Adam Santoro;David Raposo;David G. T. Barrett;Mateusz Malinowski

1443
Citations
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

David Silver;Thomas Hubert;Julian Schrittwieser;Ioannis Antonoglou

1344
Citations
Asynchronous Methods for Deep Reinforcement Learning

Volodymyr Mnih;Adrià Puigdomènech Badia;Mehdi Mirza;Alex Graves

1131
Citations
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Unknown

1033
Citations
A deep learning framework for neuroscience

Blake A Richards;Timothy P Lillicrap;Philippe Beaudoin;Yoshua Bengio;Yoshua Bengio

1032
Citations
StarCraft II: A New Challenge for Reinforcement Learning

Oriol Vinyals;Timo Ewalds;Sergey Bartunov;Petko Georgiev

889
Citations
Continuous deep Q-learning with model-based acceleration

Shixiang Gu;Timothy Lillicrap;Ilya Sutskever;Sergey Levine

889
Citations
Random synaptic feedback weights support error backpropagation for deep learning.

Timothy P. Lillicrap;Daniel Cownden;Douglas B. Tweed;Colin J. Akerman

864
Citations
Backpropagation and the brain

Timothy P. Lillicrap;Adam Santoro;Luke Marris;Colin J. Akerman

855
Citations
Vector-based navigation using grid-like representations in artificial agents

Andrea Banino;Caswell Barry;Benigno Uria;Charles Blundell

773
Citations
DeepMind Control Suite

Yuval Tassa;Yotam Doron;Alistair Muldal;Tom Erez

683
Citations
Dream to Control: Learning Behaviors by Latent Imagination

Danijar Hafner;Timothy Lillicrap;Jimmy Ba;Mohammad Norouzi

535
Citations
Experience Replay for Continual Learning

David Rolnick;Arun Ahuja;Jonathan Schwarz;Timothy P. Lillicrap

447
Citations

Frequent Co-Authors

Nicolas Heess DeepMind (United Kingdom)

David Silver DeepMind (United Kingdom)

Yuval Tassa Google (United States)

Sergey Levine University of California, Berkeley

Shixiang Gu Google (United States)

Matthew Botvinick Yale University

Demis Hassabis Google (United States)

Razvan Pascanu DeepMind (United Kingdom)

Nicholas G. Hatsopoulos University of Chicago

Stephen Scott Queen's University

External Links

Google Scholar page

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