I am currently a first-year DPhil student under the supervision of Prof. Geoff Nicholas, focusing on rankings and Bayesian inference. Prior to this, I spent five years at Alibaba as the Lead AI Data Scientist, where I led key initiatives involving large-scale AI and data platforms. I am also a qualified actuary, with two years of experience in statistical pricing at Sydney before transitioning into the tech sector.

• Partial Orders
• Statistical inference

Jesse is a second-year DPhil in Statistics student and recipient of the Clarendon Fund Scholarship. He works together with professors Frank Windmeijer and Yee Whye Teh.

Jesse's research encompasses the intersection of statistics, econometrics, and machine learning. In particular, Jesse has a strong interest in causality, the intricacies of deep learning methodologies, and their interplay in understanding complex systems.

Before starting his DPhil, Jesse graduated with distinction and cum laude from the London School of Economics and Political Science and the University of Amsterdam, focusing on econometrical and machine learning methodologies.

[e.g. educational background, biographical details]

[areas of research interest]

I am a second year StatML CDT student working on causal generative models. I previously earned an MSc in Statistical Science from the University of Oxford and a BSc from the University of Edinburgh. 

Causal generative models, data fusion, simulation.

• 2024-present: DPhil, Statistics and Machine Learning CDT, University of Oxford (Balliol College)
• 2020-2024: MMath and BA, Mathematics, University of Cambridge (Christ's College)

• Methods: Bayesian computation in multistate models
• Applications: Infectious disease epidemiology, including infection prevalence and seroprevalence data

I am a second-year DPhil student in the Department of Statistics and the Oxford-Man Institute of Quantitative Finance at the University of Oxford. I previously completed an MSc in Statistics (2022–2023) and a BSc in Mathematics and Statistics for Finance (2019–2022) at Imperial College London, where I developed a strong interest in statistical modelling and quantitative finance. Before beginning my doctoral studies, I worked as a Market Risk Analyst at JPMorgan Chase (2023–2024), where I gained valuable insights into the practical challenges of quantitative finance. My current research focuses on asset pricing anomalies and the effects of real-world trading frictions.

• Asset Pricing
• Portfolio Optimisation
• Machine Learning

I am a second year PhD student in the probability group supervised by Alison Etheridge. So far I worked on scaling limits of particle systems arising in biology, and their genealogies. 

Probabilistic modelling in population genetics

I am a DPhil student on the Health Data Science CDT working on statistical and generative machine learning for causal inference, with emphasis on applications to neuro-imaging data. Prior to starting the DPhil, I completed a BSc in Physics with Medical Physics at University College London (UCL) followed by an MPhil in Machine Learning and Machine Intelligence at the University of Cambridge.