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.
PhD Student (2nd year)
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 an 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 an 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 in videos 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.
PhD Student (1st year)
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.
PhD Student (1st year)
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.