Teaching
In reverse chronological order.
Carnegie Mellon University
Office hours, co-delivered lectures and recitations, and assignment design and grading for:
-
Deep Reinforcement Learning (10-703)
— instructed by Katerina Fragkiadaki
- Delivered a lecture on Monte Carlo, Temporal Difference Learning, Q-Learning, Deep Q-Learning, Monte Carlo Tree Search, REINFORCE, and Actor-Critic (video)
- Advanced Deep Learning (10-707) — instructed by Ruslan Salakhutdinov
- Computational Ethics for NLP (11-830) — instructed by Maarten Sap and Emma Strubell
-
Intermediate Deep Learning (10-617)
— instructed by Ruslan Salakhutdinov
- Delivered a lecture on Generative Adversarial Networks (GANs) and Graph Convolutional Networks (GCNs) (video)
- Multilingual Natural Language Processing (11-737) — instructed by Graham Neubig, Alan W. Black, and Shinji Watanabe
- Data Science Seminar (11-631) — instructed by Eric H. Nyberg and Lori Levin
The University of Edinburgh
Tutorial design and delivery, assignment grading, and lab demonstrations for:
- Introductory Applied Machine Learning (INFR10069, INFR11152) — instructed by Nigel Goddard
- Foundations of Data Science (INFR08030) — instructed by David Sterratt
- Cognitive Science (INFR08020) — instructed by Matthias Hennig
- Software Testing (INFR10057) — instructed by Ajitha Rajan