I work on neural program synthesis from input-output examples and natural language, intersections of machine learning and software engineering, and neuro-symbolic reasoning. I am particularly interested in combining neural and symbolic techniques to tackle the next generation of AI problems, including program synthesis, planning, and question answering. Notable projects of the last several years include:
- PROSE, a program synthesis framework for mass-market development of by-example technologies;
- RAT-SQL, a neuro-symbolic model for database question answering via text-to-SQL parsing.
For details on other projects, please see my CV. For recent publications, it’s best to check out my personal website, Google Scholar, or DBLP.
I completed my Ph.D. in the Paul G. Allen School of Computer Science & Engineering at the University of Washington. My advisors were Sumit Gulwani and Zoran Popović. Before joining UW, I received my B.S. in System Analysis with honors from the National Technical University of Ukraine “Kyiv Polytechnic Institute” in 2012.