I am an Assistant Professor in Computer Science at San Diego State University. My primary interest is in theoretical computer science, with a focus on problems in streaming, sublinear, parallel, and distributed models. Specifically, I'm interested in the following topics: 

• Graph, approximation, and parameterized algorithms

• Sketching algorithms for summarizing large data

• Machine learning

For more details, check out my research papers, CV , and Google Scholar. 

I completed my Ph.D. in Computer Science at the University of Massachusetts, Amherst, where I was fortunate to be advised by Andrew McGregor. I also enjoyed a year as a postdoc at Boston College, working with Hsin-Hao Su. 

Beside research, I also enjoy working on programming projects. I developed a Python library for sketching and filtering algorithms (e.g., heavy hitters, distinct counting, Bloom filters, minhash, quantile sketch). Sketching algorithms serve as tools for summarizing large data sets and can also be utilized to scale machine learning algorithms like boosted trees.