Team Members

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Edward

Johns

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Eugene

Valassakis

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Ya-Yen

Tsai

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Kamil

Dreczkowski

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Murat

Uzun

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Shikun

Liu

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Norman

Di Palo

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Vitalis

Vosylius

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I am director of the Robot Learning Lab at Imperial College. I received a BA and MEng in Electrical and Information Engineering from Cambridge University, and a PhD in vision-based robot localisation from Imperial College, working with Guang-Zhong Yang in the Hamlyn Centre. Following my PhD, I spent a year as a postdoc at UCL working with Gabriel Brostow, and I then returned to Imperial College as a founding member of the Dyson Robotics Lab with Andrew Davison, where I led the robot manipulation team. In 2017, I was awarded a Royal Academy of Engineering Research Fellowship for my project "Empowering Next-Generation Robots with Dexterous Manipulation: Deep Learning via Simulation", and then in 2018 I was appointed as a Lecturer at Imperial College, and founded the Robot Learning Lab. Alongside leading the lab's research, I teach a graduate-level course on Reinforcement Learning.

Edward Johns

Lab Director

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Eugene Valassakis

PhD Student (3rd year)

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I am a PhD student at Imperial College London, working in the Robot Learning Lab under the supervision of Dr. Edward Johns. In 2014, I received a Bachelors (BSc) with Honours in Physics  from the University of St. Andrews. After working as an Implementation Engineer at Apttus for a year, I completed a Masters (MSc) in Computer Science at Imperial College. More recently, I worked as a software developer for Prof. Kazunori Sakamoto at the National Institute of Informatics in Tokyo, and received a Masters (MSc) in Machine Learning from University College London. For my Masters dissertation, I worked under the supervision of Prof. Gabriel Brostow on predicting the future through semantic object segmentation. My current research interests lie at the crossroads of Computer Vision, Reinforcement Learning and Robotics, with particular emphasis on sim-to-real transfer for robot manipulation tasks.

Publications

CoRL 2021 Learning Eye-in-Hand Calibration from a Single Image

IROS 2021 Coarse-to-Fine for Sim-to-Real: Sub-Millimetre Precision Across Wide Task Spaces

IROS 2020 Crossing the Gap: A Deep Dive into Zero Shot Sim-to-Real Transfer for Dynamics

Ya-Yen (Charlie) Tsai

PhD Student (3rd year)

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I am currently a PhD student at Imperial College London working in the Hamlyn Centre and the Robot Learning Lab. I received my Bachelor’s in Biomedical Engineering in 2013 at University of Melbourne. Later, I received two Master’s degrees, in Mechatronics Engineering at University of Melbourne and in Medical Robotics and Image Guided Intervention at Imperial College London, both completed with Distinction. My research interest is in robot learning and adaption for complex tasks in surgical applications. The focus of the research is to achieve surgical task automation through Computer Vision, Reinforcement Learning, and Learning from Demonstrations.

Publications

ICRA 2021 DROID: Minimizing the Reality Gap Using Single-Shot Human Demonstration

ICRA 2020 Constrained Space Optimization and Reinforcement Learning for Complex Tasks

Before beginning my PhD, I completed a Bachelor’s degree in Physics and a Master’s degree in Computing (Machine Learning) at Imperial College London. During my Master’s degree I completed my individual project under the supervision of Dr. Edward Johns. The focus of this project was on learning stochastic policies from demonstrations and a sparse reward function. My PhD will extend this project and will investigate methods for robot learning of contact-rich task from demonstrations and a sparse reward function, which are both safe and efficient, and are suitable for deployment in an industrial setting.

Publications

CoRL 2021 Learning Eye-in-Hand Calibration from a Single Image

IROS 2021 Hybrid ICP

Kamil Dreczkowski

PhD Student (2nd year)

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I received my Bachelor's degree in Physics and Structural Engineering at Bogazici University, Istanbul, Turkey, in 2015. Following that, I completed my Master's degree developing system identification and damage detection algorithms at MIT. I specifically worked on Bayesian model updating methods and explored deep learning for earthquake characterization. Before joining the Robot Learning Lab as a PhD student, I led the research efforts in a computer vision startup in Berlin, which focuses on re-engineering the way humans interact with computers. I am currently working on robot manipulation and long-horizon planning for complex tasks. 

Murat Uzun

PhD Student (2nd year)

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I am a PhD student at Imperial College London working at the Dyson Robotics Lab, where I am co-supervised by Dr. Edward Johns and Prof. Andrew Davison. I completed my MRes with Distinction at the same lab working on multi-task and auxiliary learning. Prior to joining Imperial College, I obtained my BS with Honours in Mathematics and Electrical Engineering at the Penn State University. I have also interned at The Robotics Institute at Carnegie Mellon University, Tencent - YouTu Lab, and Adobe Research. My general research interest is to build learning frameworks which can induce learning algorithms automatically, with no or minimal human supervision. This includes learning a universal representation from various tasks; automating network architecture design with adaptation to different input signals; and showing a quick mastery of new tasks based on previous experiences.

Publications

ECCV 2020 Shape Adaptor: A Learnable Resizing Module

NeurIPS 2019 Self-Supervised Generalisation with Meta Auxiliary Learning

CVPR 2019 End-to-End Multi-Task Learning with Attention

Shikun Liu

PhD Student (2nd year)

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I received a BSc. in Control Engineering from University of Naples Federico II and an MSc. in AI & Robotics from Sapienza University of Rome. Over the years, I had the opportunity to work and conduct research at several institutes, startups and universities around the world. In the summer of 2017 I visited Tohoku University (Sendai, Japan), working on wheeled robots for space exploration. In the summer of 2018 I’ve been an AI research intern at Curious AI (Helsinki, Finland), where I developed state-of-the-art techniques in model-based reinforcement learning. In the summer of 2019 I conducted research at the Italian Institute of Technology (Genoa, Italy), working on quadruped robots. I joined the Robot Learning Lab first as a visiting researcher during the winter of 2019, and was then accepted for a PhD the following year. I research and design methods that allow robots and humans to collaborate in novel, intuitive and effective ways.

Publications

IROS 2021 Coarse-to-Fine for Sim-to-Real: Sub-Millimetre Precision Across Wide Task Spaces

Norman Di Palo

PhD Student (1st year)

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I am a PhD student at Imperial College London, working in the Robot Learning Lab. Prior to joining Imperial College, I received a Bachelor’s degree in Applied Physics from Vilnius University, Lithuania. Following my studies, I also carried out research with a focus on laser beam shaping. Before becoming a PhD student, I completed an MSc in Artificial Intelligence at Imperial College London. I completed my MSc individual project under the supervision of Dr. Edward Johns. During the project, I investigated ways of using Deep Learning to increase the efficiency of planning algorithms, focusing on robot motion planning. My current research interests are robot manipulation, hierarchical planning and efficient replanning for completing complex tasks.

Vitalis Vosylius

PhD Student (1st year)

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Undergraduate and Master's Students (2021-2022)

Alumni

Master's 2020 - 2021
Vadim Becquet, Jing Hu, Ivan Kapelyukh, Arjun Narula, Raul Steleac, Altan Tutar, Qianzeng Yang

Master's 2019 - 2020
Raghad Alghonaim, Omar Elkhatib, Pablo Gorostiaga Belio, Zhen Lee, Alvaro Prat Balasch, Chris Smith, Vitalis Vosylius


Master's 2018 - 2019
Steven Battilana, Sirapoab Chaikunsaeng, Zihan Ding, Kamil Dreczkowski, Mark Hartenstein, 
Fraser Price, Silvia Sapora, Georgios Theodorou, Maco Wong, Beryl Zhang, Harry Uglow


Master's 2017 - 2018
Linkun Geng, Ludovico Lazzaretti, Shikun LiuSiCong Li

Master's 2016 - 2017
Jonathan Heng, Jiaxi Liu, Diego Mendoza Barrenechea, Miklos Kepes, Rad Ploshtakov

Master's 2015 - 2016
Stephen James, Christophe Steininger