I am a post-doc at the Flatiron Institute, Center for Computational Mathematics.

My primary research objective is to develop efficient algorithms for computational problems using techniques from optimization, discrete mathematics and statistics. In particular, my research interests include

• optimization for training large language models,
• numerical and randomized linear algebra,
• large-scale and distributed convex optimization,
• learning and inference on network data,
• low-rank and structured optimization.

I received my Ph.D. in Computational Mathematics at Stanford, where I was fortunate to be advised by Stephen Boyd. Prior to my Ph.D., I received Bachelor’s in Industrial Design and Master’s in Electrical Engineering at KAIST.