Counting, Sampling, And Synthesis꞉ The Quest For Scalability
01 Feb 2023 - Kuldeep S Meel, NUS Presidential Young Professorship, School of Computing
Counting, Sampling, and Synthesis: The Quest for Scalability
Abstract
The current generation of automated symbolic reasoning techniques excel at the qualitative tasks (i.e., when the answer is Yes or No) owing to the dramatic progress in satisfiability solving, also referred to as the SAT revolution. The advances in SAT afford us the luxury to focus on quantitative reasoning tasks, whose development is critical to reason about the increasingly interconnected and complex computing systems.
In this talk, I will discuss the design of the next generation of automated reasoning techniques to perform higher-order tasks such as quantification (aka counting), sampling of representative behavior, and automated synthesis of systems. Naturally, these tasks are hard from a complexity-theoretic viewpoint, and therefore, our frameworks focus on tight integration of real-world applications, beyond the worst-case analysis algorithmic design and data-driven system design. This has allowed us to achieve significant advances in counting, sampling, and synthesis, providing a new algorithmic toolbox in formal methods, probabilistic reasoning, databases, and design verification. I will discuss the core design principles and the utility of the above techniques on various real applications, including quantitative analysis of AI systems and critical infrastructure resilience estimation
Biodata
Kuldeep Meel holds the NUS Presidential Young Professorship in the School of Computing at the National University of Singapore (NUS). His research interests lie at the intersection of Formal Methods and Artificial Intelligence. He is a recipient of the 2022 ACP Early Career Researcher Award, the 2019 NRF Fellowship for AI and was named AI’s 10 to Watch by IEEE Intelligent Systems in 2020. His research program’s recent recognitions include the 2022 CACM Research Highlight Award, 2022 ACM SIGMOD Research Highlight, IJCAI-22 Early Career Spotlight, 2021 Amazon Research Award, “Best of PODS-21” invite from ACM TODS, “Best Papers of CAV-20” invite from FMSD journal, IJCAI-19 Sister conferences best paper award track invitation.
Before joining NUS, he received M.S. and Ph.D. from Rice University, co-advised by Supratik Chakraborty and Moshe Y. Vardi. His thesis work received the 2018 Ralph Budd Award for Best Ph.D. Thesis in Engineering and the 2014 Outstanding Masters Thesis Award from Vienna Center of Logic and Algorithms, IBM Ph.D. Fellowship, and Best Student Paper Award at CP 2015. He graduated with Bachelor of Technology (with honors) in Computer Science and Engineering from IIT Bombay.