Teaching
I am very fortunate to co-supervise and mentor stellar students.
University of Cambridge (2020-2023)
- Matthew Barker, MEng in Information Engineering (Next: Trustwise)
- Vivek Palaniappan, MEng in Information Engineering (Next: Citadel)
- Katherine Collins, MPhil in Machine Learning and Machine Intelligence (Next: ML PhD at Cambridge) Departmental Thesis Distinction
- Varun Babbar, MEng in Information Engineering (Next: CS PhD at Duke) Winner of 2022 Engineering Division F Thesis Prize
- Javier Abad Martinez, Research Assistant (Next: CS PhD at ETH Zurich)
- Dan Ley, MEng in Information Engineering (Next: CS PhD at Harvard) Winner of 2021 Engineering Division F Thesis Prize
Below is a list of courses for which I was a teaching assistant.
University of Cambridge (2020-2023)
- Lent 2023: Inference (3F8) taught by Jose Miguel Hernandez-Lobato and David Krueger
- Lent 2022: Inference (3F8) taught by Richard E. Turner and David Krueger
- Michaelmas 2020: Probabilistic Machine Learning (4F13) taught by Zoubin Ghahramani and Jose Miguel Hernandez-Lobato
Carnegie Mellon University (2017-2019)
- Spring 2019: Machine Learning for Engineers - Masters (18-661) taught by Gauri Joshi
- Fall 2018: Machine Learning - PhD (10-701) taught by Ziv Bar-Joseph and Pradeep Ravikumar
- Spring 2018: Practical Data Science (15-388/15-688) taught by Zico Kolter
- Fall 2017: Data Structures and Algorithms (15-122) taught by Illiano Cervesato
- Spring 2017: Principles of Computing (15-110) taught by Margret Reid-Miller