Anthea Monod

I am an Associate Professor in Mathematics and Machine Learning at the Department of Mathematics at Imperial College London.

My research uses theory from pure mathematics (algebraic geometry and algebraic topology) to develop computational and statistical methods for data that have complex structures, or that live in complex spaces. I have applied my research to real data to solve problems in mathematical and computational biology.

I am also interested in using pure mathematics (algebraic topology and algebraic geometry) to advance our understanding of deep learning and modern AI technology. My research in this direction is supported by a £10M EPSRC Mathematical and Computational Foundations of Artificial Intelligence Hub [EP/Y028872/1]. I am a Co-Director of the Erlangen AI Hub alongside Michael Bronstein and Jeff Giansiracusa and the Imperial PI.

Research Interests:

Applied and Computational Topology including Topological Data Analysis
Applied Algebraic Geometry including Algebraic Statistics
Geometric Statistics and Machine Learning
Theoretical Machine Learning
Mathematical Biology

Contact: a [dot] monod [at] imperial [dot] ac [dot] uk
Office: Roderic Hill 318

📣 We won a £10M EPSRC grant to establish an AI Hub to study the mathematical and computational foundations of AI using geometry, topology, and algebra! You can read the press release about it here.

News & Upcoming Stuff

New preprint on the arXiv where we propose persistent homology as an interpretability tool for studying activation spaces of LLMs! Joint work with Aideen Fay, Inés García-Redondo, Qiquan Wang, and Haim Dubossarsky
New preprint where we propose entirely new graph kernels based on the genus of a graph via tropical geometry is up on the arXiv, check it out! Joint work with Yueqi Cao
Our paper on Tropical Fréchet Means has been accepted to the International Symposium on Symbolic and Algebraic Computation (ISSAC 2025) taking place this year in Guanajuato, Mexico! Joint work with Bo Lin, Kamillo Ferry, Carlos Améndola and Rudy Yoshida
New preprint on Computing the Tropical Abel–Jacobi Transform and Tropical Distances for Metric Graphs is live on the arXiv! Joint work with Yueqi Cao
New preprint on Confidence Bands for Multiparameter Persistence Landscapes up on the arXiv! Joint work with Inés García-Redondo and Qiquan Wang
In addition to being on the Scientific Advisory Committee, I will also be mentoring a project on Cycle Matching for High Dimensional Neural Activation Patterns together with Omer Bobrowski at LOGML 2025
My paper Generalized Morse Theory of Distance Functions to Surfaces for Persistent Homology has been accepted for publication in Advances in Applied Mathematics! Joint work with Anna Song and Ka Man (Ambrose) Yim
My PhD student Yueqi Cao has won a Turing Global Fellows Fund award to visit Steve Oudot's lab at INRIA next year!
My MSc student Naomi Rosenberg won a Marjorie McDermott Women's Scholarship – Congratulations, Naomi!
My term as a UKRI–EPSRC Mathematical Sciences Early Career Forum member has been extended to 2026. I am honored to continue to serve the British mathematical community by voicing the needs of early career mathematicians in the UK to the EPSRC as well as to advocate for the EPSRC within the UK mathematical landscape.

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