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Events for April 25, 2022
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CS Colloquium: Kuldeep Meel (National University of Singapore) - Counting, Sampling, and Synthesis: The Quest for Scalability
Mon, Apr 25, 2022 @ 09:00 AM - 10:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Kuldeep Meel, National University of Singapore
Talk Title: 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.
This lecture satisfies requirements for CSCI 591: Research Colloquium
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 2021 Amazon Research Award for Automated Reasoning, 2019 NRF Fellowship for AI, and was named AI's 10 to Watch by IEEE Intelligent Systems in 2020. His research program's recognition include the 2022 ACM SIGMOD Research Highlight, 2021 ICCAD Best Paper Award Nomination, "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.
Host: Mukund Raghothaman
Webcast: https://usc.zoom.us/j/99187341067WebCast Link: https://usc.zoom.us/j/99187341067
Audiences: Everyone Is Invited
Contact: Cherie Carter
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PhD Thesis Proposal - Matthew Fontaine
Mon, Apr 25, 2022 @ 10:30 AM - 12:00 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Candidate: Matthew Fontaine
Committee:
Stefanos Nikolaidis (Chair, USC, Computer Science)
Bistra Dilkina (USC, Computer Science)
Gaurav Sukhatme (USC, Computer Science)
Haipeng Luo (USC, Computer Science)
Satyandra Kumar (USC, Mechanical Engineering)
Julian Togelius (NYU, Computer Science)
Title: Towards Automating the Generation of Human-Robot Interaction Scenarios
Abstract: The human robot interaction (HRI) community currently evaluates their algorithms via hand-authored user studies. When proposing a novel algorithm, each researcher designs an experimental setup to evaluate how their new algorithm performs with human subjects. While such studies are essential to evaluating how a real human will interact with a robot, robots deployed in the real world will encounter novel scenarios not evaluated in experimental settings. To discover scenarios outside of human subjects experiments, this work proposes simulating HRI scenarios, where a scenario constitutes both an environment and simulated human agents. However, both how to explore the vast space of scenarios efficiently for diverse failures and how to generate realistic scenarios that present a feasible challenge to a human-robot team are very challenging problems. This work approaches searching the continuous space of possible scenarios as a quality diversity (QD) problem, a class of optimization problem where solving algorithms find a collection of solutions spanning a space specified by measure functions, where each solution also maximizes an objective. I present methods advancing the state-of-the-art of QD algorithms, but also a new problem setting called differentiable quality diversity (DQD) that allows for the objective and measure functions to be first order differentiable. To address the realism problem, I present methods for representing scenarios via generative models that guarantee task feasibility via mixed integer linear programming. Each of these methods is combined into an efficient scenario generation framework that tests and evaluates HRI systems. Finally, the proposed work discusses techniques for increasing the complexity of the generated scenarios and for evaluating the scenarios in real-world settings with actual end users.
WebCast Link: https://usc.zoom.us/my/tehqin?pwd=Z2E1WVp3ais1Tng1V2NndTgvR1pQQT09
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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Admitted Student Explore USC #7
Mon, Apr 25, 2022 @ 11:00 AM - 12:00 PM
Viterbi School of Engineering Undergraduate Admission
Workshops & Infosessions
We are thrilled to finally be able to meet you on campus at one of our admitted student events. During the month of April, we have seven weekday events (each called Explore USC), as well as one full-day program (called Admitted Students Day) which is scheduled for a Sunday. Please only register for one event, either an Explore USC event during the week, or the Admitted Students Day on the weekend.
Explore USC includes a Viterbi School overview, Faculty discussion from your major, lab/facility tour, lunch, and many opportunities to engage with current students.
Register here!Audiences: Everyone Is Invited
Contact: Viterbi Admission
