Graph Learning Meets Theoretical Computer Science

Location

Calvin Lab auditorium

Date

Monday, Aug. 11 – Friday, Aug. 15, 2025

Back to calendar

8:30 – 9 a.m.

Coffee and Check-In

9 – 9:10 a.m.

Welcome

9:10 – 10:30 a.m.

Boot Camp on Graph Learning

Ameya Velingker,
Haggai Maron (Technion Israel Institute of Technology and NVidia),
Christopher Morris (RWTH Aachen University)

10:30 – 11 a.m.

Break

11 a.m. – 12:30 p.m.

Boot camp on invariances in graph learning

Nadav Dym (Technion),
Risi Condor (University of Chicago),
Hannah Lawrence (MIT)

12:30 – 1:30 p.m.

Lunch

1:30 – 3 p.m.

Boot camp on graphons for graph learning

Luana Rubini Ruiz (Johns Hopkins University)

3 – 3:30 p.m.

Break

3:30 – 5 p.m.

Boot camp on graph foundations models

Mikhail Galkin (Google Research)

5 – 6 p.m.

Reception

8:30 – 9 a.m.

Coffee and Check-In

9 – 10:30 a.m.

Boot camp on logic and graph learning

Pablo Barcelo (Pontificia Universidad Catolica de Chile)

10:30 – 11 a.m.

Break

11 a.m. – 12 p.m.

A Local Graph Limits Perspective on Sampling-Based GNNs

Yeganeh Alimohammadi (University of Southern California)

12 – 1:30 p.m.

Lunch (on your own)

1:30 – 2:30 p.m.

Graph Machine Learning & Random Graph Models

Samuel Vaiter (CNRS)

2:30 – 3 p.m.

Break

3 – 4 p.m.

Homomorphism Indistinguishability

Tim Seppelt (IT University of Copenhagen)

4 – 5 p.m.

Lightning Talks

8:30 – 9 a.m.

Coffee and Check-In

9 – 10:30 a.m.

Boot camp on generalization theory for graph learning

Antonios Vasileiou (RWTH Aachen University),
Thien Le (MIT)

10:30 – 11 a.m.

Break

11 a.m. – 12 p.m.

Szemerédi Regularity Lemma in Graph Machine Learning

Ron Levie (Technion)

12 – 1:30 p.m.

Lunch (on your own)

1:30 – 2:30 p.m.

Size (OOD) Generalization of Neural Models via Algorithmic Alignment

Yusu Wang (UCSD)

2:30 – 3 p.m.

Break

3 – 4 p.m.

Toward Universal Graph Representations: Foundations and Frontiers of Graph Foundation Models

Bruno Riberio (Purdue University)

4 – 5 p.m.

Machine learning on point clouds and other varying-size objects

Soledad Villar (Johns Hopkins University)

8:30 – 9 a.m.

Coffee and Check-In

9 – 10:30 a.m.

Boot camp on CO and graph learning

Andrea Lodi (Cornell Tech)

10:30 – 11 a.m.

Break

11 a.m. – 12 p.m.

ML for discrete optimization: Theoretical foundations

Ellen Vitercik (Stanford University)

12 – 1:30 p.m.

Lunch (on your own)

1:30 – 2:30 p.m.

Exact Performance Verification of First‑Order Methods in Parametric Convex Optimization

Bartolomeo Stellato (Princeton University)

2:30 – 3 p.m.

Break

3 – 4 p.m.

Understanding ReLU Networks Through Graph Problems and Polyhedra

Christoph Hertrich (University of Technology Nuremberg)

4 – 5 p.m.

Recent trends in combinatorial optimization augmented machine learning: A graph learning perspective.

Axel Parmentier (Ecole Nationale des Ponts et Chaussées)

8:30 – 9 a.m.

Coffee and Check-In

9 – 10:30 a.m.

Bootcamp on geometry and graph learning

Anthea Monod (Imperial College London)

10:30 – 11 a.m.

Break

11 a.m. – 12 p.m.

Higher order graph neural networks with P-tensors

Risi Kondor (University of Chicago)

12 – 1:30 p.m.

Lunch (on your own)

1:30 – 2:30 p.m.

Mathematical connections of some local-to-global expressivity results over geometric graphs and point clouds

Mircea Petrache (PUC Chile)

2:30 – 3 p.m.

Break

3 – 4 p.m.

Mapping multisets to vectors

Nadav Dym (Technion)

4 – 5 p.m.

Wrap up and reflection talk

Mathias Niepert (University of Stuttgart)