Imperial College London


Faculty of EngineeringDepartment of Computing

Senior Lecturer



e.johns Website




365ACE ExtensionSouth Kensington Campus





Dr Edward Johns is the Director of the Robot Learning Lab at Imperial College London, and a Senior Lecturer (Associate Professor). His work lies at the intersection of robotics, computer vision, and machine learningand he and his team are currently studying visually-guided robot manipulation.

He received a BA and MEng in Electrical and Information Engineering from Cambridge University, and a PhD in visual place recognition from Imperial College. Following his PhD, he was a post-doc at UCL, before returning to Imperial College as a founding member of the Dyson Robotics Lab with Prof Andrew Davison, where he led the robot manipulation research.

In 2017, he was awarded a prestigious Royal Academy of Engineering Research Fellowship for his project "Empowering Next-Generation Robots with Dexterous Manipulation: Deep Learning via Simulation", and then in 2018 he was appointed as a Lecturer and founded the Robot Learning Lab. He established Imperial College's first course on Robot Learning, which he currently teaches at graduate level.

He has published over 50 peer-reviewed papers, which have over 2500 citations. In 2022 he received Imperial College's President's Award for Outstanding Early Career Researcher. Externally, he is on the advisory board for a number of robotics startups, including Karakuri and Muddy Machines, and from 2021 to 2022 he spent a year as Head of Robot Learning at Dyson in a part-time role.

Selected Publications


Johns E, Di Palo N, 2021, Learning multi-stage tasks with one demonstration via self-replay, Conference on Robot Learning (CoRL) 2021, OpenReview, Pages:1-10

Johns E, Coarse-to-fine imitation learning: robot manipulation from a single demonstration, 2021 International Conference on Robotics and Automation (ICRA), Institute of Electrical and Electronics Engineers, ISSN:1050-4729

James S, Davison A, Johns E, 2017, Transferring end-to-end visuomotor control from simulation to real world for a multi-stage task, Conference on Robot Learning, PMLR, Pages:334-343

Johns E, Leutenegger S, Davison AJ, 2016, Pairwise Decomposition of Image Sequences for Active Multi-View Recognition, Computer Vision and Pattern Recognition, Computer Vision Foundation (CVF), ISSN:1063-6919

Johns E, Leutenegger S, Davison AJ, 2016, Deep learning a grasp function for grasping under gripper pose uncertainty, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, Pages:4461-4468, ISSN:2153-0866

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