News

2024

I will be giving a keynote talk at ICTAC-24 on Automated Synthesis
Received the Manas Mandal Outstanding PhD Thesis Award at IIT Kanpur.

2023

Ph.D. Done! Successfully defended my Ph.D. thesis, “Functional Synthesis via Formal Methods and Machine Learning.”
Thankful to my amazing advisors, Kuldeep S. Meel and Subhajit Roy.
Our paper A Scalable Shannon Entropy Estimator is invited to appear in Formal Methods in System Design (FMSD) issue dedicated to the best papers from CAV 2022.

2022

Our paper on Synthesis with Explicit Dependencies has been accepted to DATE 2023. Moreover, it has also received the best paper award nomination.
We present an approach that combines advances in machine learning with automated reasoning for efficiently synthesizing functions with explicit dependencies.
Joint work with: Subhajit Roy and Kuldeep S. Meel
Excited to attend a fully packed FLoC-22. We will be presenting:
Happy to present first in-person tutorial :) We will be talking about automated synthesis at IJCAI-22.
I am attending Highlights of Logic, Games and Automata. I will be talking about our work on program synthesis as dependency quantified formulas. Also, looking forward to visit Pierre Marquis and Daniel Le Berre as a part of Highlights Extended Stay Program.
I am visiting Simons institute to attend the reunion for Satisfiability: Theory, Practice, and Beyond program. I will be presenting our work on program synthesis as dependency quantified formulas.
Our work on A Scalable Shannon Entropy Estimator is accepted to CAV-22.
We propose the first efficient algorithmic technique to estimate the Shannon entropy of a specification with PAC-style guarantees, i.e., the computed estimate is guaranteed to lie within a (1 ± ε)-factor of the ground truth with confidence >= 1−δ.
Joint work with: Brendan Juba and Kuldeep S. Meel
Our work On Quantitative Testing of Samplers has been accepted to CP-22.
We design a computational hardness-based tester, called ScalBarbarik. ScalBarbarik provides a qunatitative way to analysis the quality of a sampler.
Joint work with: Mate Soos, Sourav Chakraborty, Kuldeep S. Meel
Join, from the comfort of your home, our tutorial on Automated Synthesis: Towards the Holy Grail of AI at AAAI-22.

2021

I will be giving a student invited talk at iVerif: Workshop on artifical intelligence and Verification . Its a pre-FSTTCS workshop. See you all at FSTTCS!
Our paper on Engineering an Efficient Boolean Functional Synthesis Engine has received the best paper nomination at ICCAD 21
I will be visiting Daniel Neider (MPI-SWS), Armin Biere (University of Freiburg) in two weeks from now! Hoping to visit CISPA as well to meet Bernd Finkbeiner.
Our paper Engineering an Efficient Boolean Functional Synthesis Engine has been accepted to ICCAD 2021.
The work addresses scalability barriers faced by the current state-of-the-art synthesis techniques. We propose four algorithmic improvements for a data-driven framework for functional synthesis.
Joint work with: Friedrich Slivovsky, Subhajit Roy and Kuldeep S. Meel
Our paper Designing Samplers is Easy: The Boon of Testers has been accepted to FMCAD 2021.
Our Sampler not only passes the tests of Barbarik but also leads to significant performance improvements for real-world instances.
Joint work with: Mate Soos, Sourav Chakraborty, Kuldeep S. Meel
Excited to announce that I will presenting a talk on synthesis at the 32nd, European Summer School in Logic, Language, and Information.
Our paper on Program Synthesis as Dependency Quantified Formula Modulo Theory has been accepted to IJCAI 2021.
We show that theory-constrained synthesis can be reduced DQF(T), i.e., to the problem of finding a witness of a dependency quantified formula modulo theory.
Joint work with: Subhajit Roy and Kuldeep S. Meel

2020

We presented a data-driven approach for Boolean functional synthesis, which works at the intersection of constrained sampling, machine learning and automated reasoning at CAV 2020.
Presented a talk on a data driven approach for Boolean function synthesis at 4th Workshop on Learning in Verification (LiVe), ETPAS, 2020 and at Software Engineering Research in India, SERI, 2020.
We have released the source code of Manthan.
Our paper on A data-driven approach for Boolean function synthesis has been accepted to CAV-20
Joint work with: Subhajit Roy and Kuldeep S. Meel