I lead the Graph AI Applications team at Katana Graph, a start-up founded by Prof. Keshav Pingali and Prof. Chris Rossbach in 2020. Our team works on developing end-to-end machine learning pipelines on Katana’s large-scale distributed Graph AI platform.

Before joining Katana Graph, I have spent a couple of years as a postdoctoral researcher at UC Santa Cruz where I worked with Prof. C. Seshadhri. I obtained my Ph.D. in Computer Science from Dartmouth College, advised by Prof. Amit Chakrabarti.

In the past, I have worked at IBM Research Lab and Adobe India.

Research Interests

I am broadly interested in the topic of large-scale machine learning. My current research involves developing scalable graph AI models for real-world applications. I also work on designing efficient and practical graph algorithms with theoretical guarantees in various Big Data models such as the streaming/distributed models. Over the past few years, I have enjoyed working on a diverse range of topics including algorithmic fairness, scalable clustering, communication complexity, arithmetic circuit complexity, and approximation algorithms. My research has been published at premier theoretical computer science conferences such as SODA, ITCS, ICALP, etc. as well as at top-tier ML/data mining conferences such as NeurIPS, KDD, TheWebConference (previously known as WWW), VLDB, etc.

For more details, see my publications.