Educational game that prepares kids for the crazy AI future by teaching them to create awesome stuff with modern AI right now.

Co-advisors: Yoshua Bengio and Ioannis Mitliagkas

I worked in the area of generalization in deep learning. My main work revolved around pointing out that the bias-variance tradeoff hypothesis is not always correct.Advisor: Ioannis Mitliagkas

I did research in deep learning at Montreal Institute for Learning Algorithms. The two areas I worked in during my internship were generative models and MCMC sampling in Bayesian inference.Advisor: Yoshua Bengio

Causal AI, large language models, and misc other AI

Teaching 10-14 year olds how to do awesome stuff with cutting-edge AI (e.g. LLMs, diffusion models, zero-to-few-shot image/NLP classifiers etc.)

Worked with various AI tools (LLMs, chatbots, misc other NLP) to build a product to help people make better decisions fasterWebsite: https://www.oogway.ai

- Popular course (900K video views on YouTube) used by many people- Lectures, slides, and accompanying course textbook at causalcourse.com

Working on fundamental and applied research in causal inference

I was a teaching assistant for the first offering of the Big Data Analytics graduate course. My responsibilities included preparing and teaching recitations, helping prepare homeworks, and grading. I gave an hour and half long talk on more advanced parts of deep learning for this course.

I worked on research that involved the development of and application of Multi-View Convolutional Neural Networks to computer vision. I was advised by Subhransu Maji.

I did research with Dr. Sampath Kannan in computer science theory.

I was a teaching assistant for the undergraduate algorithms course.

- Brought together hundreds of students and 30+ tutors in math and sciences- Tutored math, science, and computer science