معرفی
Suguman Bansal is an Assistant Professor in the School of Computer Science at Georgia Institute of Technology. Her research focuses on formal methods and their applications to artificial intelligence, programming languages, and machine learning. Previously, she held an NSF/CRA Computing Innovation Postdoctoral Fellowship at the University of Pennsylvania (2020-2022) and completed her PhD at Rice University (2016-2020).
Education:
- PhD in Computer Science, Rice University (2016-2020)
- MS in Computer Science, Rice University (2014-2016)
- BSc (Honors) in Mathematics and Computer Science, Chennai Mathematical Institute (2011-2014)
Research Interests: Formal methods, reinforcement learning, reactive synthesis, quantitative verification, and trustworthy AI systems. Her work bridges logic-based formal methods with modern AI challenges, emphasizing safety, reliability, and generalization in AI systems.
Key Contributions: Pioneering work on specification-guided reinforcement learning, compositional synthesis algorithms, and formal verification of AI systems. Notable tools include Lisa (LTLf synthesis tool) and DiRL (compositional reinforcement learning framework).
Awards: 2020 NSF CI Fellowship, 2021 MIT EECS Rising Star, 2023 ATVA Best Paper Award, and Keynote Speaker at SAS 2022.
Advising & Grants: Advises PhD and Master’s students in reinforcement learning and formal methods. Lead PI on a collaboration grant with IIT Bombay (2024) and recipient of a ~$250K NSF/CRA postdoctoral grant.
Labs/Teams: Leads the BansalLab at Georgia Tech, focusing on trustworthy AI through formal methods and algorithmic innovation.
