I am a PhD student at Imperial College London, supervised by Edward Johns at The Robot Learning Lab. My research interests
include robot manipulation and the broader field of robot learning.
Before joining Imperial for my MSc in AI and subsequently my PhD, I studied Applied Physics
and worked on advancing laser beam engineering techniques at the Center for Physical Sciences and Technology.
I also spent time as a research intern at the Dyson Robot Learning Lab, led by Stephen James.
Recently, I was honoured to receive the Imperial College Robotics Forum - Amazon PhD Prize for Outstanding Achievement in Robotics for my PhD research.
If you would like to get in touch to chat or collaborate with me, feel free to send me an
e-mail!
My research interests lie in the areas of robot learning and manipulation. Specifically, I
focus on algorithmically improving sample efficiency and generalisation capabilities of
imitation learning frameworks. This allows robots to acquire useful manipulation skills more
effectively from limited data and adapt to new tasks and settings quickly.
Below are some of my projects that illustrate my efforts in this area.
We formulate In-Context Imitation Learning as a graph generation problem and use
procedurally generated pseudo-demonstrations as a main source of training data, achieving
manipulation skill acquisition instantaneously after the provided demonstrations.
We introduce R&D, a method that integrates RGB observations with low-level actions through
3D renders of the robot and iteratively updates them using a learnt denoising process,
significantly improving learning efficiency and spatial generalisation.
