I’ve just finished my graduate studies. After spending 2.5 years in the PhD program at the database group, at UW Allen School of Computer Science, advised by Dan Suciu, I decided to leave with M.S and work in industry. During my PhD, I focused on data systems and machine learning, specifically on join processing, and natural languge interfaces for querying knowledge graphs.

Brief bio

Prior to moving to UW, I studied Mathematics and Computer Science at UCLA. There, I was fortunate to work with Guy Van den Broeck and do research on inference in probabilistic models as a member of Statistical Relational AI Lab. During all four years, I taught mathematics to a group of high-school students at the UCLA Olga Radko Endowed Math Circle. I was also part of Upsilon Pi Epsilon, and DevX - a student-led organization focusing on building useful things for the community at UCLA. We built an app that tracks crowdedness of libraries on campus in real time.

Work experience

I’ve also worked in a bunch of places!

Most recently, I interned at RelationalAI, where I was integrating a novel query compiler into the main query processing engine. RelationalAI team is fantastic!

I also worked at AWS Redshift for two summers in a row. First time, I worked on bringing ML into the data warehouse. It was a very fun internship! Next summer, I returned to Redshift again; this time, I was working on optimizing autoscaling configurations as a step to enable Redshift Serverless. I also interned at NAND Capital, a trading startup, which was an exciting experience learning about financial markets. Here, I primarily researched and implemented options pricing models and ivol prediction. Finally, I interned at Yandex optimizing the logic for establishing TLS handshakes.

I grew up in Moscow, Russia.

Publications