[AI Seminar Series] Seminar by Suqi Liu, Friday March 6th, 12-1pm, MRB Seminar Room

[Vassilis Tsotras]

The next AI Seminar will be on Friday March 6th, 12-1pm, in the MRB Seminar
Room (1st floor).

The talk will be given by *Prof. Suqi Liu*, Department of Statistics, UCR

*** 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-1984239271074


TITLE: Graph Neural Network Meets Random Geometric Graph

ABSTRACT:
Graph neural networks (GNNs) have emerged as a powerful framework for
learning from graph-structured data, yet their theoretical
understanding—particularly regarding the behavior of different
architectural choices across various graph-based tasks—remains limited. In
parallel, random geometric graphs (RGGs) provide a well-defined
probabilistic model that captures the interplay between geometry and
connectivity in complex networks.

In this talk, I will discuss several efforts I have undertaken to bridge
these two perspectives by studying GNNs through the lens of RGGs. In the
first part, I will focus on the classic graph matching problem and show
that, by leveraging a specific GNN, perfect recovery can be achieved even
in high-noise regimes. In the second part, I will briefly highlight recent
work demonstrating the provable benefits of graph attention networks (GATs)
for a node regression task. This talk is based on joint work with Morgane
Austern, Kenny Gu, and Somak Laha.


Bio:
Suqi Liu is an Assistant Professor in the Department of Statistics at the
University of California, Riverside. He received his Ph.D. in Operations
Research and Financial Engineering from Princeton University. Prior to
joining UCR, he was a Postdoctoral Research Fellow in Biomedical
Informatics at Harvard University. His research interests lie at the
intersection of probability, statistics, and artificial intelligence, with
applications in biomedical sciences.

------------------------------------
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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