(she/her/hers)
IITK and NUS
Automated Reasoning and Synthesis
Golia is a fifth year PhD student at Indian Institute of Technology Kanpur and National University of Singapore, advised by Prof. Kuldeep S. Meel and Prof. Subhajit Roy. Her research interest lies in the area of Boolean Functional Synthesis, Constraint Solving and Sampling, and Knowledge Compilation. She is the lead designer of the state-of-the-art functional synthesis engine, Manthan.
Functional Synthesis: Machine Learning meets Formal Methods
Given a specification F(X,Y) over the set of input variables X and output variables Y, we want the assistant, aka functional synthesis engine, to design a function G such that (X,Y=G(X)) satisfies F. Functional synthesis has been studied for over 150 years, dating back Boole in 1850's and yet scalability remains a core challenge. Motivated by progress in machine learning, we design a new algorithmic framework Manthan, which views functional synthesis as a classification problem, relying on advances in constrained sampling for data generation, and advances in automated reasoning for a novel proof-guided refinement and provable verification.
On an extensive and rigorous evaluation over 609 benchmarks, we demonstrate that Manthan significantly improves upon the current state of the art, solving 509 benchmarks in comparison to 280, which is the most solved by a state of the art technique. The significant performance improvements, along with our detailed analysis, highlights several interesting avenues of future work at the intersection of machine learning, constrained sampling, and automated reasoning.