I am working part-time as a Teaching Scholar in the Department of Computing while doing my PhD. Since 2022, I have a Postgraduate Certificate in University Teaching and Learning and I am a Fellow of the Advance Higher Education. These are some of my contributions:
Computation Techniques - Course leader
In 2022, I was Course leader for the Computation Techniques 2nd-year Undergraduate course. I was teaching the basis of Linear Albegra to ~110 students, giving the plenary lectures, designing the material, organising the lab sessions, and setting up the exams. We made all our materials available on the Course website. In particular, I am really proud of the Linear Algebra Lecture notes I designed for this lecture.
Reinforcement Learning - Lead Teaching Assistant
For two years in a row, in 2022 and 2021, I was also Lead Teaching Assistant for the MSc Reinforcement Learning lecture. It was a massive lecture with ~350 students. I was in charge of designing all coursework and lab-assignments, doing some of the Q&A sessions, organising lab-session, and coordinating the 25 teaching-assistants. Here is, as an example, the first lab-assigmment of the lecture that I fully designed to help the students understand the basics of MDP.
Mathematics - Tutor
Throughout my PhD, I was also a tutor for small group maths tutorials for First Year Undergraduates. These tutorials aim to teach undergraduate students the basics of Analysis and Linear Algebra.
Supervision
Over the past years, I have been co-supervising 3 MSc 3 MEng and 1 UROP students with my PhD advisor Dr Antoine Cully, working on Quality-Diversity and Deep Reinforcement Learning algorithms.
Other Teaching activities
I was also a Teaching Assistant in various lectures including C++, Robot Learning and Control, Introduction to Machine Learning, Machine Learning for Imaging, etc.
I designed part of the second coursework for the Introduction to Machine Learning MSc and MEng lecture (~450 students). Jointly with the lecturers, we designed a coursework to guide the students in building their own pytorch-like neural network Python library, and try it on a simple regression task using the California House Prices Dataset.