[Bphystudent] [Ssb_members] Fwd: AI/Scientific Computing Seminar Talk by Prof. Daniele E. Schiavazzi, Friday May 1st, 12-1pm, MRB Seminar Room

[Navaira Sherwani via SSB_members]

Hi everyone,

Apologies for the previous email. It posted as a wall of black text. Here's
the actual email!

Hope to see you there!

Best,
Navaira Sherwani
________________________________________________________________________________________________________________

---------- Forwarded message ---------
From: Vassilis Tsotras <vassilis.tsotras at ucr.edu>
Date: Sat, Apr 25, 2026 at 2:15 PM
Subject: [AI Seminar Series] Seminar by Prof. Daniele E. Schiavazzi, Friday
May 1st, 12-1pm, MRB Seminar Room
To: <raise-seminar at lists.ucr.edu>


The next AI Seminar will be on Friday May 1st, 12-1pm, in the MRB Seminar
Room (1st floor).

*** Pizza and refreshments will be provided ****

To keep track of the number of attendees, please *register* at:
https://www.eventbrite.com/e/ai-seminar-series-tickets-1988215879216

The talk will be given by *Prof. Daniele E. Schiavazzi,* Department of
Applied and Computational Mathematics and Statistics, University of Notre
Dame
This talk is co-sponsored by RAISE at UCR Institute and Interdisciplinary
Center for Data-driven Modeling in Biology.

TITLE: Model Synthesis for Scientific Agents

ABSTRACT:
Applications of generative modeling and deep learning in physics-based
systems have traditionally focused on building emulators - computationally
inexpensive approximations of input-to-output maps. However, the remarkable
flexibility of data-driven architectures opens opportunities to broaden
their scope to include model inversion and identifiability analysis. We
present InVAErt networks, a framework for data-driven analysis and
synthesis of parametric physical systems. Through numerical experiments, we
demonstrate the framework's versatility across a wide range of problems,
including linear systems of equations, spatio-temporal PDEs, and
lumped-parameter physiological models. We further introduce an extension
for systems with observational noise, enabling the separation of structural
from practical identifiability in complex ill-posed inverse problems.
Finally, we discuss recent efforts to integrate InVAErt networks with large
language model agents for applications in cardiovascular health.


Bio:
Dr. Schiavazzi is an Associate Professor in the Applied and Computational
Mathematics and Statistics Department, and a Concurrent Associate Professor
in the AME Department at the University of Notre Dame. He graduated with
honors and received a Ph.D. degree in Applied Mathematics from Universita'
degli Studi di Padova, Italy. Dr. Schiavazzi completed his Ph.D. thesis as
a Visiting Researcher at Stanford University, followed by a Postdoctoral
position at University of California, San Diego and Stanford University.
His main research interests are in stochastic analysis, multi-resolution
approximation, numerical modeling and finite element analysis, adaptive
Markov chain Monte Carlo estimation and use of computational models to
inform clinical decision making under uncertainty.

------------------------------------
Sponsored by the RAISE at UCR Institute, the AI Seminar Series presents
speakers working on cutting edge Foundational AI or applying AI in their
research. The goal of these seminars is to inform the UCR community about
current trends in AI research and promote collaborations between faculty in
this emerging field. These seminars are open to interested faculty and
graduate/undergraduate students. Please forward this email to other
colleagues or students in your lab that may be interested. After the seminar a
discussion will follow for questions, open problems, ideas for possible
collaborations etc.

Sincerely,
Vassilis Tsotras
Professor, CSE Department
co-Director, RAISE at UCR Institute

Amit Roy-Chowdhury
Professor, ECE Department
co-Director, RAISE at UCR Institute
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