Kuldeep S. Meel

Registered user since Tue 19 Feb 2019

Name: Kuldeep S. Meel

Bio: Kuldeep Meel is an Assistant Professor of Computer Science in School of Computing at the National University of Singapore where he holds the Sung Kah Kay Assistant Professorship. He received his Ph.D. (2017) and M.S. (2014) degree in Computer Science (Artificial Intelligence and Formal Methods) from Rice University. He holds B. Tech. (with Honors) degree (2012) in Computer Science and Engineering from Indian Institute of Technology, Bombay. His research interests lie at the intersection of Artificial Intelligence and Formal Methods. Meel has co-presented tutorials at top-tier AI conferences, IJCAI 2018, AAAI 2017, and UAI 2016. His work received the 2018 Ralph Budd Award for Best PhD Thesis in Engineering, 2014 Outstanding Masters Thesis Award from Vienna Center of Logic and Algorithms and Best Student Paper Award at CP 2015. He received the IBM Ph.D. Fellowship and the 2016-17 Lodieska Stockbridge Vaughn Fellowship for his work on constrained sampling and counting.

Affiliation: National University of Singapore

Personal website: https://www.comp.nus.edu.sg/~meel/

Research interests: Formal Methods in Artificial Intelligence

Contributions

SPIN 2021 National University of Singapore, Singapore in Programming Committee within the SPIN-track
ESEC/FSE 2020 Author of Baital: An Adaptive Weighted Sampling Approach for Improved t-wise Coverage within the Research Papers-track
ICSE 2021 Author of Scalable Quantitative Verification For Deep Neural Networks within the Technical Track-track
SPIN 2019 Author of Constrained Counting and Sampling: From Theory to Practice and Back within the 26th International SPIN Symposium on Model Checking of Software-track
TACAS 2019 Author of WAPS: Weighted and Projected Sampling within the TACAS 2019-track
ETAPS 2019 Author of WAPS: Weighted and Projected Sampling within the Posters-track
VMCAI 2018 Author of Scalable Approximation of Quantitative Information Flow in Programs within the VMCAI 2018-track