Si-Qi LIU Senior Research Engineer @ DeepMind MPhil/PhD @ UCL, London
Previously CentraleSupélec, University of Oxford.


During the day I'm a Research Engineer at DeepMind where I work on challenging open problems in machine learning and artificial intelligence. My current focus sits at the intersection of Reinforcement Learning, Multi-Agent, Game Theory and Continuous Control.

I grew up in China, moved to France in 2011 to study and I'm now living and working in London.


Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity

Marta Garnelo, Wojciech Marian Czarnecki, Siqi Liu, Dhruva Tirumala, Junhyuk Oh, Gauthier Gidel, Hado van Hasselt, David Balduzzi

AAMAS 2021 | paper

dm_control: Software and Tasks for Continuous Control

Saran Tunyasuvunakool, Alistair Muldal, Yotam Doron, Siqi Liu, Steven Bohez, Josh Merel, Tom Erez, Timothy Lillicrap, Nicolas Heess, Yuval Tassa

Journal | paper | code

V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control

H Francis Song, Abbas Abdolmaleki, Jost Tobias Springenberg, Aidan Clark, Hubert Soyer, Jack W Rae, Seb Noury, Arun Ahuja, Siqi Liu, Dhruva Tirumala, Nicolas Heess, Dan Belov, Martin Riedmiller, Matthew M Botvinick

ICLR 2020 | paper

A Generalized Training Approach for Multiagent Learning

Paul Muller, Shayegan Omidshafiei, Mark Rowland, Karl Tuyls, Julien Perolat, Siqi Liu, Daniel Hennes, Luke Marris, Marc Lanctot, Edward Hughes, Zhe Wang, Guy Lever, Nicolas Heess, Thore Graepel, Remi Munos

ICLR 2020 | paper

Emergent Coordination through Competition

Siqi Liu, Guy Lever, Josh Merel, Saran Tunyasuvunakool, Nicolas Heess, Thore Graepel

ICLR 2019 | paper | website | code

Hierarchical Visuomotor Control of Humanoids

Josh Merel, Arun Ahuja, Vu Pham, Saran Tunyasuvunakool, Siqi Liu, Dhruva Tirumala, Nicolas Heess, Greg Wayne

ICLR 2019 | paper | demo

Reinforcement Learning Agents acquire Flocking and Symbiotic Behaviour in Simulated Ecosystems

Peter Sunehag, Guy Lever, Siqi Liu, Josh Merel, Nicolas Heess, Joel Z Leibo, Edward Hughes, Tom Eccles, Thore Graepel

ALIFE 2019 | paper

The Body is not a Given: Joint Agent Policy Learning and Morphology Evolution

Dylan Banarse, Yoram Bachrach, Siqi Liu, Chrisantha Fernando, Nicolas Heess, Pushmeet Kohli, Guy Lever, Thore Graepel

AAMAS 2019 | paper

Observational Learning by Reinforcement Learning

Diana Borsa, Nicolas Heess, Bilal Piot, Siqi Liu, Leonard Hasenclever, Remi Munos, Olivier Pietquin

AAMAS 2019 | paper

Improved Image Captioning via Policy Gradient Optimization of SPIDER

Siqi Liu, Zhenhai Zhu, Ning Ye, Sergio Guadarrama, Kevin Murphy

ICCV 2017 | paper | oral


Mar 2017 - Present
Senior Research Engineer @ DeepMind
Jul 2016 - Nov 2016
Research Intern @ Google Research
Machine Intelligence (Mountain View)
Jun 2015 - Sep 2015
Software Engineer Intern @ Google
Adwords Optimization (New York)
Feb 2015 - Jun 2015 (part-time)
Consultant Engineer @ Collabora Ltd
LibreOffice for Android
Jun 2014 - Sep 2014
Software Engineer Intern @ Google
Knowledge Graph (Zurich)


MPhil/PhD in Artificial Intelligence & Neuroscience.
2015 - 2016
MSc in Computer Science, with distinction.
2013 - 2016
MEng (Diplôme d'Ingénieur), classement A (1st)
2011 - 2013
Génie Informatique, GPA 4.99/5