GLOW is a new reading group designed to foster discussions on the foundations and latest developments in Graph Machine Learning.

We meet (once a month) on Wednesdays at 5 pm CET

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Upcoming Event

30th September 2026

On the trade-off between expressivity and privacy in graph representation learning

Patrick Indri, Tamara Drucks, Thomas Gärtner

Unifying Graph Neural Networks Through a Common Layer Equation

Sai Karthik Navuluru, Siddhartha Shankar Das, Bo Ni, Hongjie Chen, Yu Wang, Baris Coskunuzer, Nesreen K. Ahmed, Franck Dernoncourt, Mahantesh Halappanavar, Tyler Derr, Ryan A. Rossi, Lakshman Tamil

14th October 2026

The first GLOW poster session

Instead of the usual setup, we are organising a big Gather Town session where you can present a poster about your own graph-related ideas, project or paper. People can move around the space, drop into conversations, listen to pitches, and discuss — much more informal and exploratory!

This is open to everyone: whether you've been working on something for a while or want feedback on your early-stage ideas, there's a spot for you.

Applications are still open! If you’d like to claim a space in Gather Town, please fill in this form before October 7th: Googleform

See you there!🚀

Our Concept

GLOW aims to create an inclusive and accessible environment that encourages interaction, especially for junior researchers and those outside major research labs.

Interactive Discussions: Unlike traditional reading groups dominated by long presentations, GLOW emphasizes small group discussions, breakout rooms, and active participation.
Diverse Formats: Our sessions will rotate through various formats, including 30-minute paper presentations followed by discussions, expert panel deep dives on specific topics, interview-style Q&A sessions with authors, and spotlight sessions for spontaneous brainstorming or early-stage ideas.
Thematic Focus: We plan to explore big themes over multiple sessions, such as invariance, expressivity, and the role of transformers in graph learning.