I am a SMARTbiomed Senior Research Fellow, jointly based at the Big Data Institute (BDI) and the Department of Statistics. I co-lead the Biobank Rare-Variant Consortium (BRaVa), a collaborative effort involving 16 biobanks and cohorts (to date) from around the world to analyse rare genetic variation at scale to identify the genetic underpinnings of complex traits and disorders. I also co-lead the (gen)omics theme at the BDI.

I received an integrated master's degree in Mathematics and Statistics from the University of Warwick and a DPhil in Statistics from the University of Oxford, supervised by Professor Dame Angela McLean and Professor Gil McVean. I subsequently worked as a postdoctoral researcher with Professor Ben Neale, Dr Nick Patterson, and Professor Cecilia Lindgren at Massachusetts General Hospital, the Broad Institute, and the University of Oxford.

I develop and apply statistical and computational methods to gain insight into disease mechanisms. I am particularly interested in combining genetic, phenotypic and functional data to better refine association signals and understand the genetic architecture of complex traits. To this end, I collaborate with international partners to assemble and analyse large public datasets of human genetic variation.

As genetic sequencing datasets continue to grow, the tools we use must grow with them. My work also focuses on building scalable methods and computational approaches to analyse massive genetic datasets.

I am a third-year PhD student with broad interests in probability theory, branching processes, random structures, and models from statistical physics. My current research focuses on the limiting behaviour of certain branching Brownian motion particle systems. Before starting my DPhil, I completed graduate studies at École Polytechnique and the University of Cambridge.

• Branching processes
• Brownian motion and random walks
• Statistical physics

Although my research is primarily theoretical, probabilistic reasoning arises naturally in many problems. I especially enjoy discovering simple and visual arguments. I am always open to collaboration-please feel free to reach out!

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I am a DPhil student in Statistics supervised by Prof. Pier Palamara. My primary interest is in complex trait analysis and association studies in large genomic datasets. Previously, I completed my Bachelor’s degree in Statistics and Computer Science at McGill University and an MSc in Statistical Science at the University of Oxford.

Statistical and population genetics; complex trait analysis; scalable methods for association studies in large genomic datasets.

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 first-year DPhil in Statistics student and recipient of the Clarendon Fund Scholarship. He works together with professors Frank Windmeijer, Ruixun Zhang, and Mihai Cucuringu.

Jesse's research encompasses the intersection of statistics, econometrics, and machine learning. In particular, Jesse has a strong interest in causality, the intricacies of machine and 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.

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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)

My goal is to use statistics and machine learning approaches to gain insights in infectious disease epidemiology.