Statistical learning
Probabilistic modelling, and generative methods for high-dimensional data.
Related workML and Statistics
Associate Lecturer
UCL Institute of Finance & Technology
Exploring interconnected systems through machine learning and quantum-inspired models of uncertainty.
01 / Research
My research focuses on machine learning and quantum-inspired models, with an emphasis on learning from varied data and representing uncertainty.
Probabilistic modelling, and generative methods for high-dimensional data.
Related workExploring quantum-inspired approaches to learning, representation, and modelling systems with interacting parts.
Related workFROM THE RESEARCH NOTEBOOK
Notes on modelling choices, geometric intuition, and the assumptions worth looking twice at.
Some thoughts on inducing points, conditional dependence, and choosing between SVGP and Vecchia approximations.
Response perturbations, marginal-likelihood curvature, and why a large residual does not necessarily imply large parameter influence.
A worked explanation of when cross-task contributions cancel, and what changes with noise, incomplete observations and shared fitting.
Observation contexts, order-dependent probabilities, and how ordinary data can enter a quantum-inspired latent model.
02 / Publications
SSRN · Posted October 2026
SSRN · Posted October 2026
International Journal of Data Science and Analytics · 22, article 316
Economic Analysis and Policy · 93, 1215–1240
SSRN · Written December 2025; revised August 2026
arXiv:2511.21515 · November 2025; revised March 2026
Journal of Econometrics and Statistics · 5(2), 215–235
AAAI Bridge 2023: AI for Financial Institutions · Conference presentation
International Journal of Computational Linguistics · 13(2), 18–25
Handbook on Entropy, Complexity and Spatial Dynamics: A Rebirth of Theory? · Chapter 19 · Edward Elgar
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03 / Contact
For academic correspondence and research enquiries.