[FM-India] IARCS Verification Seminar Series -- Talk by Suguman Bansal on October 5, 1900 hrs IST

[VSS IARCS]

Dear all,

The next talk in the IARCS Verification Seminar Series will be given by
Suguman Bansal, an NSF/CRA Computing Innovation Postdoctoral Fellow at the
University of Pennsylvania. The talk is scheduled on Tuesday, October 5, at
1900 hrs IST. The details can be found on the webpage (
https://fmindia.cmi.ac.in/vss/), and also appended to the body of this
email.

The Verification Seminar Series, an initiative by the Indian Association
for Research in Computing Science (IARCS), is a monthly, online
talk-series, broadly in the area of Formal Methods and Programming
Languages, with applications in Verification and Synthesis. The aim of this
talk-series is to provide a platform for Formal Methods researchers to
interact regularly. In addition, we hope that it will make it easier for
researchers to explore newer problems/areas and collaborate on them, and
for younger researchers to start working in these areas.

All are welcome to join.


Best regards,
Deepak, Madhukar, Rahul, Srivathsan


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Title: Reactive synthesis from Quantitative Constraints: An Automata
Approach

Meeting Link:
https://us02web.zoom.us/j/89164094870?pwd=eUFNRWp0bHYxRVpwVVNoVUdHU0djQT09
(Meeting ID: 891 6409 4870, Passcode: 082194)

Abstract: Reactive synthesis is the automated construction, from a
high-level description of its desired behavior, of a reactive system that
continuously interacts with an uncontrollable external environment. The
success of reactive synthesis from qualitative constraints calls for the
question of whether one can perform synthesis from more expressive
specifications?

In this talk, I will discuss the problem of reactive synthesis from
quantitative constraints, referring to quantitative behaviors of systems
such as rewards, costs, resources consumption, etc. The mention of
quantitative properties may conjure up images of approaches that use
numerical methods - optimization, linear programming, min-max games, and so
on. In a paradigm shift, I will introduce a novel, purely automata-based
approach to solve the synthesis problem whilst offering theoretical and
practical improvements over the existing numerical methods-based
state-of-the-art.

These significant improvements open the door for automata-based solutions
in formal quantitative reasoning with exciting applications in planning and
reinforcement learning.


Bio: Suguman Bansal is an NSF/CRA Computing Innovation Postdoctoral Fellow
at the University of Pennsylvania, mentored by Prof. Rajeev Alur. Her
research goal is on advancing Assured Autonomy using formal methods and
programming languages to design-develop-deploy safe AI systems.

She is the recipient of the 2020 NSF CI Fellowship and has been named a
2021 MIT EECS Rising Star. Her research has appeared at venues including
AAAI, CAV, TACAS, and POPL. She completed her Ph.D. in 2020, advised by
Prof. Moshe Y. Vardi, from Rice University. She received B.S. with Honors
in 2014 from Chennai Mathematical Institute.