Fabio Pardo

Fabio Pardo

PhD Student in Machine Learning

Imperial College London
London, SW7 1NA
United Kingdom


fabiopardo @pardofab

I am a PhD student in the Robot Intelligence Lab at Imperial College London.
My main research focuses on Deep Reinforcement Learning.


2016 – present
PhD in Machine Learning
Deep Reinforcement Learning
@ Imperial College, London, UK
2014 – 2015
Master's degree in Computer Science
AI, ML, Robotics
@ Pierre et Marie Curie University, Paris, France
2012 – 2014
Master’s degree in Cognitive Science
Neuroscience, Cognitive Psychology, Computational Modeling, Neuroimaging, AI
@ École Normale Supérieure Ulm, EHESS and Descartes University, Paris, France
2009 – 2012
Bachelor's degree in Computer Science
@ Pierre et Marie Curie University, Paris, France


Learning to plan
André Barreto, Théophane Weber, Arthur Guez, Peter Humphreys, Timothy Lillicrap, Mehdi Mirza
@ DeepMind (Reinforcement Learning team), London, UK
Motor primitives and competitive self-play
Raia Hadsell, Nicolas Heess, Josh Merel and Leonard Hasenclever
@ DeepMind (Deep Learning team), London, UK
Deep reinforcement learning for autonomous robot navigation from vision
Tetsunari Inamura
@ National Institute of Informatics, Tokyo, Japan
Multimodal concepts emergence for a humanoid robot in interaction with a human tutor
David Filliat
@ Flowers laboratory, Inria and ENSTA ParisTech, Paris, France
Video and video
Optimal decision making based on a mixture of prediction experts
Homeostatic engine for reinforcement learning agents
Laurent Orseau
@ Inria and AgroParisTech, Paris, France
Ontology visualization methods and their impact on short-term memory storage in humans
Jean-Gabriel Ganascia
@ Lip6, Paris, France


OstrichRL: A Musculoskeletal Ostrich Simulation to Study Bio-mechanical Locomotion
Vittorio La Barbera*, Fabio Pardo*, Yuval Tassa, Monica Daley, Christopher Richards, Petar Kormushev, John Hutchinson (* equal contribution)
@ NeurIPS' deep RL workshop 2021
Paper, poster, Website and code
Ivy: Templated Deep Learning for Inter-Framework Portability
Daniel Lenton, Fabio Pardo, Fabian Falck, Stephen James, Ronald Clark
Paper, website and code

Tonic: A Deep Reinforcement Learning Library for Fast Prototyping and Benchmarking
Fabio Pardo
@ NeurIPS' deep RL workshop 2020
Paper, poster, code and data
CoMic: Complementary Task Learning & Mimicry for Reusable Skills
Leonard Hasenclever, Fabio Pardo, Raia Hadsell, Nicolas Heess, Josh Merel
@ ICML 2020
Paper and code
Scaling All-Goals Updates in Reinforcement Learning Using Convolutional Neural Networks
Fabio Pardo, Vitaly Levdik, Petar Kormushev
@ AAAI 2020
@ NeurIPS 2018 Deep RL Workshop
@ ICML 2018 Exploration in RL Workshop
Paper, poster, website and code
Time Limits in Reinforcement Learning
Fabio Pardo, Arash Tavakoli, Vitaly Levdik, Petar Kormushev
@ ICML 2018
@ NIPS 2017 Deep RL Symposium
Paper, poster and website
Action Branching Architectures for Deep Reinforcement Learning
Arash Tavakoli, Fabio Pardo, Petar Kormushev
@ AAAI 2018
@ NIPS 2017 Deep RL Symposium
Paper and poster


2018 – present
Organizer of Imperial's deep reinforcement learning reading group
Weekly meetings to discuss papers (contact me if you want to join)
@ Imperial College, London, UK
2016 – 2018
Graduate teaching assistant in Computing and Robotics
Lectures, tutorials, exams
@ Imperial College, London, UK
2011 and 2012
Twice finalist of Prologin, the French national programming contest
Algorithmic tests and 36-hour hackathon
@ École Polytechnique and EPITA, Paris, France