I am a second-year PhD student in Computer Science at Stanford University advised by Chris Piech. My research interests are in probabilistic reasoning, theory, and building intelligent systems that help humans learn.
I previously completed my Bachelor's in Mathematics, also at Stanford, advised by Kannan Soundararajan. During that time, I lectured a class on standard C++ programming!
I love teaching and thinking about fun theoretical problems. I keep a blog on the side where I write about random Maths, CS, and Philosophy related gems that come my way.
Here are some links to the class websites of the courses I have taught at Stanford so far. If you have any questions or suggestions for improvements, please feel free to email me!
Proceedings of the 39th International Conference on Machine Learning (ICML), Balitmore, USA. 2022
Proceedings of the 35th Annual Conference on Learning Theory (COLT), London, UK. 2022
Proceedings of the 14th International Conference on Educational Data Mining (EDM), Paris, France. 2021
Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (SIGCSE), (Virtual) USA, 2021.
Proceedings of the 34th AAAI Conference on Artificial Intelligence, New York, USA. 2020.
Proceedings of the 36th International Conference on Machine Learning (ICML), Long Beach, USA. 2019
Proceedings of the 12th International Conference on Educational Data Mining (EDM), Montréal, Canada. 2019
A secure, reliable, cross-platform desktop application to administer computerised examination for large classes. Has been used to administer over 5000 exams in Stanford's introductory CS classes.
Exploring the effectiveness of deep generative recurrent networks in the task of understanding and generating motion. In particular, we attempt to generate GIFs of realistic mechanical motion on a synthetic dataset from an initial seed frame.