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)

• ACP Early Career Award, 2022 [Press1] [Press2]
• IJCAI-22 Early Career Spotlight, 2022
• AI's 10 to Watch by IEEE Intelligent Systems, 2020
• 2019 NRF Fellowship for AI [Press]
• 2018 Ralph Budd Award for research in Engineering. This award, established in 1935, is given annually for the best doctoral thesis in the School of Engineering.
• Honorable mention for 2018 ACP Doctoral Dissertation Award
• IBM PhD Fellowship (2016-17)
• Lodieska Stockbridge Vaughn Fellowship (2016-17), awarded to upto five students university wide whose record at Rice shows evidence of outstanding achievement and promise.
• 2014 Outstanding Masters Thesis Award from the Vienna Center for Logic and Algorithms

Research Paper Recognition

• CAV-24 Paper received Distinguished Paper Award.
• ICLP-24 Paper received Best Paper Award.
• ICDT-24 Paper invited to LMCS Issue dedicated to the best papers from ICDT 2024
• CACM Research Highlights (2023)
• CAV-23 paper received Distinguished Paper Award and invited to FMSD issue dedicated to the best papers from CAV 2023
• DATE-23 paper received Best Paper Award Nomination
• Knuth's Note on ESA-22 Paper
• ACM SIGMOD Research Highlight (2022)
• CAV-22 Paper invited to FMSD issue dedicated to the best papers from CAV 2022
• ICCAD-21 paper received Best Paper Award Nomination (6 out of 121 papers)
• CAV-20 Paper invited to FMSD issue dedicated to the best papers from CAV 2020
• CP 2018 paper invited to IJCAI-19 Sister Conferences Best Paper Award Track
• Best Student Paper Award, CP 2015
• CP 2013 paper selected as one of the 25 papers across 25 years of CP anniversary volume (2019).

Teaching Recognition

• NUS (university-level) Annual Teaching Excellence Award, 2023; Recent Student Feedback: [CS4244] [CS3243]
• NUS (university-level) Annual Teaching Excellence Award, 2022
• School of Computing Faculty Teaching Honor Roll, 2023-27;
• School of Computing Faculty Teaching Excellence Award, 2023;
• School of Computing Faculty Teaching Excellence Award, 2022
• School of Computing Faculty Teaching Excellence Award, 2021

Software Recognition

• Model Counting Competition
• 2024: 1st place in All Three Tracks
• 2023: 1st place in Projected Model Counting Track
• 2022: 1st place in Model Counting Track and Projected Model Counting Track
• 2021: 2nd place in Model Counting Track
• 2020: 1st place in Model Counting Track and Projected Model Counting Track
• 2nd place in EDA Challenge 2021
• 3rd place in SAT competition 2020

• PhD Students: Md Mohimenul Kabir; Yash Pote; Uddalok Sarkar (co-advised with Sourav Chakraborty); Arijit Shaw ; Jack Sun; Yifan Ruan; Yang Suwei; Jiong Yang
• Post-docs: Dr. Paulius Dilkas;

PhD Graduates

1. Teodora Baluta (2024), co-advised with Prateek Saxena
   PhD Thesis: Rigorous Security Analysis of Machine Learning Systems
   Next Position: Assistant Professor, Georgia Institute of Technology
2. Dr. Priyanka Golia (2023), co-advised with Prof. Subhajit Roy
   PhD Thesis: Functional Synthesis via Formal Methods and Machine Learning
   Next Position: Assistant Professor, (CISPA and then IIT Delhi)
3. Dr. Bishwamittra Ghosh (2023)
   PhD Thesis: Interpretability and Fairness in Machine Learning: A Formal Methods Approach
   Next Position: Post-doc, Max Planck Institute for Software Systems, Saarbrucken, Germany

• Dr. Mate Soos, Senior Research Fellow (Mar-June 2024; Mar-June 2023; Jul-Sep 2019; Mar-June 2018)

1. Dr. Anna Latour (Feb 2022-Apr 2024)
   Next Position: Assistant Professor at Delft University of Technology
2. Dr. Timothy van Bremen (June 2022-June 2024)
   Next Position: Assistant Professor at Nanyang Technological University (NTU), Singapore
3. Dr. Gunjan Kumar (March 2021-July 2024)
   Next Position: Assistant Professor at IIT Kanpur
4. Dr. Lawqueen Kanesh (Jan 2021-Dec 2021)
   Now: Assistant Professor, IIT Jodhpur
5. Dr. Jaroslav Bendik (Jan 2021-Apr 2021)
   Next Position: Post-doc at MPI-SWS; Current Position: Team Lead at Certora
6. Dr. Vignesh Sivaraman (Sep 2020-Apr 2021)
   Now: Assistant Professor at IIIT Hyderabad.
7. Dr. Yong Lai (Aug 2019-Aug 2020)
   Next Position: Associate Professor at Jilin University

1. Alexis de Colnet, MComp@NUS (Graduated: Dec 2018); now post-doc at TU Wien
2. Rahul Gupta, BTech+MTech@IITK ( co-advised with Subhajit Roy (IITK)
3. Shubham Sharma, BTech+MTech@IITK (Graduated: May 2019), co-advised with Subhajit Roy (IITK)
4. Delannoy Remi Christian, MComp@NUS, (Graduated: Dec 2019)
5. Lorenzo Ciampiconi, MS@Politecnico di Milano (Graduated: Dec 2019)

• Research Topic
• Year
• Publication Type

• CSC2512: Advanced Propositional Reasoning (Fall 2023)
• CS3243: Introduction to Artificial Intelligence (Spring 2024; Fall 2021; Fall 2020)
• CS 4244: Knowledge Representation and Reasoning (Spring 2023; Spring 2021; Spring 2020; Spring 2019; Spring 2018)
• CS 4269/5469: Fundamentals of Logic in Computer Science (Fall 2019)
• CS 6283: Advanced Topics in Computer Science: Logic in AI (Fall 2018)

• Program Co-Chair: SAT 2022
• Co-organizer:
  • Beyond Satisfiability at Simons's Institute Program on Satisfiability: Theory, Practice, and Beyond
  • (Co-chair) CP 2020 Doctoral Program
  • Workshop on Counting and Sampling (since 2020)
  • (Sponsorship Co-chair) KR 2021
  • 1st Workshop on Probabilistic Reasoning and Formal Methods
  • Indian SAT-SMT Winter School (since 2019).
• Recent Program Committee: SAT-22 (Program Co-chair), PODS-24, ICML-23 (AC), CAV-23, SAT-23, IJCAI-23 (SPC), AISTATS-23 (AC), FMCAD-23, AAAI-23, FoSSaCS-23, AAAI-22 (SPC),FMCAD-22, IJCAI-22 (AC), CAV-22, NeurIPS-21 (AC), IJCAI-21 (SPC), AAAI-21 (SPC), FMCAD-21
• Awarded Distinguished Program Committee Member for IJCAI 2018.

• Counting, Sampling, and Synthesis: The Quest for Scalability [slides] [video](@NUS)
• Functional Synthesis: An Ideal Meeting Ground for Formal Methods and Machine Learning [slides] [video](@Wisconsin)
• Approximate Counting and Sampling [slides] [video] (@Simons Institute)
• The Rise of Approximate Model Counting: Beyond Classical Theory and Practice of SAT [slides] [video](@Simons Institute)

• 10 December 2024

  We have three papers accepted to AAAI-25.

  The first paper takes a step towards real-time approximate model counting. Joint work with Jiong Yang and Yash Pote.

  The second paper focuses on probabilistic explanations for linear models. Joint work with Bernardo Subercaseaux and Marcelo Arenas.

  The third paper focuses on projected and incremental pseudo-boolean model counting. Joint work with Suwei Yang.

• 11 October 2024

  Our ICLP paper received Best Paper Award at ICLP-24. Joint work with Mahi Kabir. Congratulations Mahi!

• 22 July 2024

  Our CAV-22 paper received Distinguished Paper Award. This is second consecutive Distinguished Paper Award for our group at CAV and both of these papers are led by Jiong. Congratulations Jiong!

• 11 July 2024

  Our paper analyzing the performance of model counting tools in the wild is accepted to KR 2024. We showcase the limitations of competition results in predicting the performance for benchmarks arising in practice.

All news…