<div dir="auto"><div class="gmail_quote" dir="auto"><div dir="ltr" class="gmail_attr">Hi everyone, </div><div dir="ltr" class="gmail_attr"><br></div><div dir="ltr" class="gmail_attr">Apologies for the previous email. It posted as a wall of black text. Here's the actual email! </div><div dir="ltr" class="gmail_attr"><br></div><div dir="ltr" class="gmail_attr">Hope to see you there! </div><div dir="ltr" class="gmail_attr"><br></div><div dir="ltr" class="gmail_attr">Best,</div><div dir="ltr" class="gmail_attr">Navaira Sherwani</div><div dir="ltr"><div class="gmail_quote"><div dir="ltr"><div class="gmail_quote"><div dir="ltr"><div class="gmail_quote"><div dir="ltr"><div>________________________________________________________________________________________________________________<div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">---------- Forwarded message ---------<br>From: <strong class="gmail_sendername" dir="auto">Vassilis Tsotras</strong> <span dir="auto"><<a href="mailto:vassilis.tsotras@ucr.edu" rel="noreferrer noreferrer noreferrer" target="_blank">vassilis.tsotras@ucr.edu</a>></span><br>Date: Sat, Apr 25, 2026 at 2:15 PM<br>Subject: [AI Seminar Series] Seminar by Prof. Daniele E. Schiavazzi, Friday May 1st, 12-1pm, MRB Seminar Room<br>To: <<a href="mailto:raise-seminar@lists.ucr.edu" rel="noreferrer noreferrer noreferrer" target="_blank">raise-seminar@lists.ucr.edu</a>><br></div><br><br><div dir="ltr"><div dir="ltr"><div class="gmail_quote"><div dir="ltr" class="gmail_attr">The next AI Seminar will be on Friday May 1st, 12-1pm, in the MRB Seminar Room (1st floor).</div><div dir="ltr"><div dir="ltr"><div dir="ltr"><div class="gmail_quote"><div dir="ltr"><div dir="ltr"><div class="gmail_quote"><div dir="ltr"><div class="gmail_quote"><div dir="ltr"><div dir="ltr"><div class="gmail_quote"><div dir="ltr"><div dir="ltr"><div class="gmail_quote"><div dir="ltr"><div class="gmail_quote"><div dir="ltr"><div dir="ltr"><div class="gmail_quote"><div dir="ltr"><div dir="ltr"><div class="gmail_quote"><div dir="ltr"><div><br></div><div>*** Pizza and refreshments will be provided ****<br><br>To keep track of the number of attendees, please *register* at:</div><div><a href="https://www.eventbrite.com/e/ai-seminar-series-tickets-1988215879216" rel="noreferrer noreferrer noreferrer" target="_blank">https://www.eventbrite.com/e/ai-seminar-series-tickets-1988215879216</a></div><div><br></div><div>The talk will be given by <b>Prof. Daniele E. Schiavazzi,</b> Department of Applied and Computational Mathematics and Statistics, University of Notre Dame<br>This talk is co-sponsored by RAISE@UCR Institute and Interdisciplinary Center for Data-driven Modeling in Biology.<br><br></div><div>TITLE: Model Synthesis for Scientific Agents</div><div><br></div><div>ABSTRACT: </div><div>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.</div><div><br></div><div><br></div><div>Bio:</div><div>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.</div><div><br></div><div>------------------------------------<br>Sponsored by the RAISE@UCR Institute, the <span><span><span>AI</span></span></span> <span><span><span>Seminar</span></span></span> <span><span><span>Series</span></span></span> presents speakers working on cutting edge Foundational <span><span><span>AI</span></span></span> or applying <span><span><span>AI</span></span></span> in their research. The goal of these <span><span><span>seminars</span></span></span> is to inform the UCR community about current trends in <span><span><span>AI</span></span></span> research and promote collaborations between faculty in this emerging field. These <span><span><span>seminars</span></span></span> 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 <span><span><span>seminar</span></span></span> a discussion will follow for questions, open problems, ideas for possible collaborations etc.<br><br>Sincerely,<br>Vassilis Tsotras<br>Professor, CSE Department<br>co-Director, RAISE@UCR Institute<br><br>Amit Roy-Chowdhury<br>Professor, ECE Department<br>co-Director, RAISE@UCR Institute</div></div>
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