Biography
I am a Data Science Research Fellow at the Heilbronn Institute for Mathematical Research. I completed my PhD at the School of Mathematics, University of Bristol supervised by Prof. Patrick Rubin-Delanchy.
My research interests include using graph embeddings to find interesting structure in real-world networks.
- Graph embedding for clustering, anomaly detection and link prediction
- Applications in cyber-security, social science and biology
PhD in Statistics, 2022
University of Bristol
Certificate in Advanced Study of Mathematics (Part III), Distinction, 2005
University of Cambridge, Trinity College
BA Hons. Mathematics, First, 2004
University of Cambridge, Trinity College
Publications
Recent & Upcoming Talks
Neural Information Processing Systems (NeurIPS 2023), New Orleans, USA, December 2023. Intensity profile projection: a framework for continuous-time representation learning for dynamic networks.
NUMBATs Seminar, Monash University, Australia, September 2023. Adjacency spectral embedding beyond unweighted, undirected networks.
Mathematical and Statistical Aspects of Security and Cybersecurity, Bristol, UK, May 2023. Spectral graph embedding for computer networks.
International Conference on Computational Statistics (COMPSTAT 2022), Bologna, Italy, August 2022. Spectral embedding of weighted graphs.
Neural Information Processing Systems (NeurIPS 2021), Virtual, December 2021. Spectral embedding for dynamic networks with stability guarantees.
Software
I have written a Python package for graph spectral embedding available at the GitHub repository, Spectral-Embedding.
The package includes a variety of tools for spectral embedding of graphs, using the theory of the generalised random dot product graph and its many extensions to analyse networks.
Teaching
Statistical Machine Learning, University of Bristol, 2022/23.
Contact
- ian.gallagher@bristol.ac.uk
- Office GA.09, Fry Building, School of Mathematics, University of Bristol, Bristol, UK, BS8 1TW