Hi, I'm Shyamal, a final-year Computer Science PhD student in the Theory of Computation Group at Columbia University. My research interests are in computational learning theory, property testing, and sublinear algorithms. I am fortunate to be advised by Cliff Stein and Xi Chen and supported by an NSF Graduate Fellowship.

I'm broadly interested in questions such as:

1. Given labeled data, how much time do algorithms need to learn a high-accuracy hypothesis that predicts the labels of (unlabelled) examples?

2. Given query access to a function, how many queries do we need to determine if it's structured?

3. What metrics are well-approximated by the shortest paths of a sparse graph?

Some specific problems I have thought about are learning intersections of halfspaces, learning DNF, tolerant junta testing, distribution-free testing of boolean functions, and spanners.