ECE seminar: Counting, sampling, and synthesis: the quest for scalability

Tuesday, March 22, 2022 10:00 am - 10:00 am EDT (GMT -04:00)

Speaker: KULDEEP S. MEEL, NATIONAL UNIVERSITY OF SINGAPORE

Topic: COUNTING, SAMPLING, AND SYNTHESIS: THE QUEST FOR SCALABILITY

Date: TUESDAY, MARCH 22, 2022

Time: 10:00 am – 11:00 am

Zoom: https://uwaterloo.zoom.us/j/96802948854?pwd=eElmZEMweVU3b2kzNU5IdzdqWUgvUT09

Meeting ID: 968 0294 8854

Passcode: 812687

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.

Biography:

Kuldeep Meel holds the NUS Presidential Young Professorship in the School of Computing at the National University of Singapore. His research interests lie at the intersection of Formal Methods and Artificial Intelligence. He is a recipient of the 2019 NRF Fellowship for AI and was named AI's 10 to Watch by IEEE Intelligent Systems in 2020. His research program's recognition includes the 2022 ACM SIGMOD Research Highlight, 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. He holds a 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 PhD Fellowship, and Best Student Paper Award at CP 2015.

All are welcome!