In parallel with my PhD, I was working part-time as a Teaching Scholar in the Department of Computing at Imperial College. In 2022, I completed a Postgraduate Certificate in University Teaching and Learning and became a Fellow of the Advance Higher Education.

Supervision

During my PhD, I co-supervised MSc, MEng, and UROP students together with my PhD advisor, Prof Antoine Cully, on projects focused on Quality-Diversity and Deep Reinforcement Learning algorithms. As a postdoc, I have continued co-supervising students with my PI, Prof Amanda Prorok, on multi-agent learning projects.

Computation Techniques - Course leader

In 2022, I was Course Leader for the Computation Techniques second-year undergraduate course, teaching the foundations of Linear Algebra to a cohort of about 110 students. This included delivering plenary lectures, designing teaching materials, organising laboratory sessions, and setting examinations. We made all the material available on the Course website. In particular, the Linear Algebra Lecture notes I wrote for this course are something I put real care into, and I’m still proud of them.

Reinforcement Learning - Lead Teaching Assistant

In 2021 and 2022, I was Lead Teaching Assistant for the MSc Reinforcement Learning lecture, taken by around 350 students each year. My responsibilities included designing coursework and laboratory assignments, leading Q&A sessions, organising laboratory classes, and working with a team of 25 teaching assistants. As an example, here is the first lab-assignment of the lecture, which I designed to help students understand the basics of Markov Decision Processes (MDPs).

Other Teaching activities

Throughout my PhD, I also tutored small-group mathematics tutorials for first-year undergraduates, focusing on the basics of Analysis and Linear Algebra.

In addition, I served as a Teaching Assistant for a range of lectures, including C++, Robot Learning and Control, Introduction to Machine Learning, and Machine Learning for Imaging.