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Kuldeep S. MeelNUS Presidential Young ProfessorAssistant Professor School of Computing National University of Singapore CV: [pdf] | Research Statement: [pdf] Teaching: [pdf] | Bio: [txt] |
Research Group Office: COM2-03-41 Email: meel@comp.nus.edu.sg Twitter: @ksmeel Tools: Github Publications: [html] [pdf] External: [Scholar] [DBLP] |
Kuldeep Meel holds NUS Presidential Young Professorship in the School of Computing at the
National University of Singapore. He is a receipient 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.
His research interests are at the intersection of formal methods and artificial intelligence. His research program's long-term vision is to advance automated reasoning techniques to enable computing to deal with increasingly uncertain real-world environments. Check out Research Statement and publications for more details.
Our research group is still growing. Check out Open Positions.
External Funding: National Research Foundation, AI Singapore, Grab NUS AI Lab, Microsoft Research Asia, Ministry of Education, Defense Service Organization
I am married to fellow computer science professor Suguman Bansal.Our paper on Probabilistic Query Complexity in Combined Complexity is accepted to PODS-23. Joint work with Timothy van Bremen
Our paper on “Testing Horn Samplers” is accepted to AISTATS-23. The paper is co-authored with Anshuman Banerjee, Sourav Chakraborty, Uddalok Sarkar, and Sayantan Sen.
Our paper on synthesis with explicit dependencies is accepted to DATE-23. The paper also received Best Paper Award Candidate nomination. Co-authored with Priyanka Golia and Subhajit Roy. Priyanka is on on academic job market.
Two papers accepted to AAAI-23. The first paper, co-authored with Pavan Aduri, N.V. Vinodchandran, and Arnab Bhattacharyya, focuses on constraint optimization over semirings. The second paper, co-authored with Yong Lai and Roland Yap, focuses on fast converging model counting.