Suguman Bansal

My research interests lies in Formal Methods and Logic, and their applications to Artificial Intelligence, Machine Learning, and Programming Languages. The long-term research goal is to build Trustworthy AI by simplifying the design-development-deployment pipeline of safe and reliable AI systems.

My current research thrusts include:

• Formal Methods for Reinforcement Learning
• Reactive Synthesis from High-Level Specifications
• Symbolic Quantitative Reasoning

Previously, I was an NSF/CRA Computing Innovation Postdoctoral Fellow at the University of Pennsylvania, mentored by Rajeev Alur. I completed my Ph.D. at Rice University, advised by Moshe Y. Vardi and obtained my undergraduate degree from Chennai Mathematical Institute.

note for GaTech students interested in research

I work with students after they demonstrate strong performance in one of my courses. If you are interested in working with me, please register for CS 8803 LCS (Logic in Computer Science, Syllabus) in Fall 2026.

teaching

• CS 8803 (LCS): Logic in Computer Science — Fall 2026 (Upcoming, Syllabus), Fall 2023
• CS 8803 (FMR): Formal Methods in Reinforcement Learning — Fall 2025
• CS 4510: Automata and Complexity — Fall 2025, Spring 2024, Spring 2023

selected awards and honors Full list

• CACM Article (Research and Advances) 2026 on Specification-Guided Reinforcement Learning
• Amazon Research Award 2025
• Best Paper Award, ATVA 2023
• 🥉 3rd Place, LTLf Realizability Track, SYNTCOMP 2023 (Tool: Lisa)
• Invited Tutorial Speaker at 28th Joint Conference on ETAPS 2025
• Keynote Speaker at 44th Conference on FSTTCS 2024
• Keynote Speaker 29th Static Analysis Symposium (SAS 2022)
• NSF/CRA Computing Innovation Fellow 2020
• MIT EECS Rising Star (2021, 2018)