Projects

I am currently working on projects involving the use of reinforcement learning to generate useful, interpretable data for mathematicians in combinatorics and convex geometry to inform conjectures and proofs. More details to come!

This is a blog for my project on the applications of machine learning to discover causal relationships in data in Fall 2022. How can we use machine learning to uncover causal relationships in the world?

During my work in the data science bootcamps at the Erdos Institute, I worked on two projects with a team of very cool collaborators in projects in data science in machine learning.

I worked with Daniel Pimentel-Alarćon on a project on approximating incomplete data with varieties. If there’s some unknown data that we think has linear structure and we only have access to noisy low dimensional projections (think - an unknown (linear) object in a dark room and I only show you the shadows after we shine a light), how accurately can we reconstruct the original unknown data?