Fabio Pardo PhD Student in Machine Learning Imperial College London London, SW7 1NA United Kingdom f.pardo[at]imperial.ac.uk

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

Education

	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

Internships

	2021 Learning to plan André Barreto, Théophane Weber, Arthur Guez, Peter Humphreys, Timothy Lillicrap, Mehdi Mirza @ DeepMind (Reinforcement Learning team), London, UK
	2019 Motor primitives and competitive self-play Raia Hadsell, Nicolas Heess, Josh Merel and Leonard Hasenclever @ DeepMind (Deep Learning team), London, UK
	2015 Deep reinforcement learning for autonomous robot navigation from vision Tetsunari Inamura @ National Institute of Informatics, Tokyo, Japan
	2014 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
	2013 Optimal decision making based on a mixture of prediction experts Homeostatic engine for reinforcement learning agents Laurent Orseau @ Inria and AgroParisTech, Paris, France
	2013 Ontology visualization methods and their impact on short-term memory storage in humans Jean-Gabriel Ganascia @ Lip6, Paris, France

Research

	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

Miscellaneous

	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