Advances in Data Science and AI seminar: Petar Veličković

Part of the Institute for Data Science and AI Seminars collection. The Advances in Data Science and AI seminar series showcases innovative research in data science and AI from across the world.

Abstract: When deploying graph neural networks, we often make a seemingly innocent assumption: that the input graph we are given is the ground-truth. However, as my talk will unpack, this is often not the case: even when the graphs are perfectly correct, they may be severely suboptimal for completing the task at hand. This will introduce us to a rich and vibrant area of graph rewiring, which is experiencing a renaissance in recent times. I will discuss some of the most representative works, including two of our own contributions (https://arxiv.org/abs/2210.02997, https://arxiv.org/abs/2306.03589), one of which won the Best Paper Award at the Graph Learning Frontiers Workshop at NeurIPS'22.

Petar Veličković, Staff Research Scientist, Google DeepMind and Affiliated Lectureship at the University of Cambridge

Petar Veličković is a Research Scientist at DeepMind. He holds a PhD degree from the University of Cambridge (obtained under the supervision of Pietro Liò), with prior collaborations at Nokia Bell Labs and Mila. His current research interests broadly involve devising neural network architectures that operate on nontrivially structured data (such as graphs), and their applications in algorithmic reasoning and computational biology.

Petar has published his work in these areas at both machine learning venues (ICLR, NeurIPS-W, ICML-W) and biomedical venues and journals (Bioinformatics, PLOS One, JCB, PervasiveHealth). In particular, he is the first author of Graph Attention Networks, a popular convolutional layer for graphs, and Deep Graph Infomax, a scalable local/global unsupervised learning pipeline for graphs. His research has been featured in media outlets such as ZDNet. Additionally, he has co-organised workshops on Graph Representation Learning at ICLR 2019 and NeurIPS 2019.

This seminar is hosted in partnership with ID Manchester and Turing Innovation Catalyst as part of the official AI Fringe.

‍

‍Agenda:

13:45 - Registration and Arrival

14:00 - Welcome and introductions with Dr Julia Handl, Professor of Decision Sciences at the University of Manchester

14:10 - Petar Veličković, Staff Research Scientist, Google DeepMind and Affiliated Lectureship at the University of Cambridge (Graph Neural Networks / Geometric deep learning.)

14:45 - Q&A

15:00 - Networking

15:30 - Event close