I hold Stephen Fleming Early-Career Associate Professorship in the School of Computer Science, and an Associate Professor at the University of Toronto (on leave). Prior to moving to Toronto, I held NUS Presidential Young Professorship (at the rank of Assistant Professor) in the School of Computing at the National University of Singapore. I am a recipient of 2019 NRF Fellowship for AI (accompanied with SGD 2.6 million funding), ACP 2022 Early Career Researcher Award, and was named AI's 10 to Watch by IEEE Intelligent Systems in 2020. I love teaching, and I am proud to be recipient of university-level Teaching Excellence Awards at NUS in 2022 and 2023. A longer version of bio is available here.
My primary research interest is in automated reasoning. The long term vision of my research program's is to advance automated reasoning techniques to enable computing to deal with increasingly uncertain real-world environments. The core theme of my research program is the quest for scalability. Accordingly, our work straddles theory and practice, and draws upon ideas from randomized algorithms, statistical inference, formal methods, distribution testing, and software engineering.
Given the broad nature of the field of automated reasoning, my research group's work spans multiple traditional subfields of computer science, reflected by publication record as well as recognition in artificial intelligence (AAAI: 17×, IJCAI:13×, NeurIPS: 6×), formal methods (CAV: 7×, CP: 8×, SAT: 6×, TACAS:3×), design automation (ICCAD: 2x, DATE: 2x, DAC: 1x), and logic/databases (PODS: 4x, ICALP:1x, LPAR:4x, LICS: 2x). In short, a research group that is not bound by (traditional) borders.
Check out Research Statement (last updated: Dec 2021) and publications for more details.
External Funding: National Research Foundation, AI Singapore, Grab NUS AI Lab, Microsoft Research Asia, Ministry of Education, Defense Service Organization (Singapore)
Personal: I am married to fellow computer science professor Suguman Bansal. Some more info: here and hereFour of my advisees were in job market this past academic year and all of them managed to secure tenure-track positions in four countries across three continents. Congratulations!
Our paper characterizing the complexity of total variation distance estimation and probabilistic inference is accepted to ICML 2024. Our paper shows that estimating TV distance admits FPRAS if the underlying inference queries can be performed in polynomial time.
Our paper on engineereing an efficient preprocessor for model counting is accepted to DAC 2024. Joint work with Mate Soos.
We have two papers accepted to PODS-24.
The first paper, co-authored with Sourav Chakraborty]sourav and Umang Mathur presents a faster FPRAS for counting the number of words accepted by NFA.
The second paper, co-authored with Pavan Aduri,Sourav Chakraborty, and N.V. Vinodchandran introduces the model of right to be forgotten in the context of streaming.