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Current Lab Members
Chris Holmes
My research explores the potential of computational statistics and statistical machine learning to assist in the medical and health sciences. In this respect I oversee a small research group working on probabilistic models and Bayesian decision analysis in complex biomedical data environments. This includes theoretical foundations, novel methodology, and “hands-on” study driven data science.
I hold a joint Statutory Professorship (Oxford speak for Chair) in Biostatistics at the departments of Statistics and the Nuffield Department of Medicine. Within the Nuffield medical school I am an Affiliate Member of the Li Ka Shing Centre for Health Information and Discovery. My research is partly funded through a Programme Leaders award in Statistical Genomics from the UK's Medical Research Council. I am Scientific Director for the Health Programme at the Alan Turing Institute, London.
I hold a joint Statutory Professorship (Oxford speak for Chair) in Biostatistics at the departments of Statistics and the Nuffield Department of Medicine. Within the Nuffield medical school I am an Affiliate Member of the Li Ka Shing Centre for Health Information and Discovery. My research is partly funded through a Programme Leaders award in Statistical Genomics from the UK's Medical Research Council. I am Scientific Director for the Health Programme at the Alan Turing Institute, London.
Anna Menacher
I'm Anna. I'm a DPhil Student in the StatML CDT who is supervised by Chris Holmes and Thomas Nichols. My PhD is partially funded by Novartis which is why I am part of the Neuroimaging Group at the Big Data Institute as well as the Stats Department at the University of Oxford.
I'm currently working on large scale binary lesion modeling via a hierarchical Bayesian spatial model with structured variable selection.
I'm currently working on large scale binary lesion modeling via a hierarchical Bayesian spatial model with structured variable selection.
Fabian Falck
I completed an MSc in Computing Science at Imperial College London in 2018. Since then, I have worked in academia as a research engineer in robotics and computer vision at Imperial College London and as a research assistant in statistical machine learning at Carnegie Mellon University and the University of Oxford before joining the PhD programme. I also co-organised the Machine Learning for Health workshop at NeurIPS in 2019 and 2020.
I am particularly interested in the theory and application of machine learning models to tackle impactful problems in Healthcare and the wider biomedical domain. In my free time, I enjoy singing, playing the guitar and any racket sport you throw at me, particularly tennis and badminton.
I am particularly interested in the theory and application of machine learning models to tackle impactful problems in Healthcare and the wider biomedical domain. In my free time, I enjoy singing, playing the guitar and any racket sport you throw at me, particularly tennis and badminton.
Lucile Ter-Minassian
I'm a PhD student looking at Causal Inference & Bayesian Machine Learning
Natalia Garcia-Martin
I am a PhD student at the [EPSRC & MRC Centre for Doctoral Training (CDT) in Next Generational Statistical Science](http://www.oxwasp-cdt.ac.uk/epsrc--mrc-centre-for-doctoral-training.html) funded by CRUK.
I am supervised by [David Wedge](https://www.bdi.ox.ac.uk/Team/david-wedge), [Jens Rittscher](http://www.ibme.ox.ac.uk/research/biomedia/jens-rittscher), [Chris Holmes](http://www.stats.ox.ac.uk/~cholmes) and [Heba Sailem](http://www.ibme.ox.ac.uk/research/biomedia/people/dr-heba-sailem) and work on the integration of Genomics and Image Analysis for the study of cancer subtypes to predict tumour behaviour and response to treatment using Statistical Machine Learning.
I am supervised by [David Wedge](https://www.bdi.ox.ac.uk/Team/david-wedge), [Jens Rittscher](http://www.ibme.ox.ac.uk/research/biomedia/jens-rittscher), [Chris Holmes](http://www.stats.ox.ac.uk/~cholmes) and [Heba Sailem](http://www.ibme.ox.ac.uk/research/biomedia/people/dr-heba-sailem) and work on the integration of Genomics and Image Analysis for the study of cancer subtypes to predict tumour behaviour and response to treatment using Statistical Machine Learning.
Oscar Clivio
First, after the Prépa Track, I did my undergrad in mathematics and computer science at Ecole des Ponts ParisTech, in France. After this followed my master’s degree in machine learning at Ecole normale supérieure Paris-Saclay. I wrote my master's thesis following an internship at UC Berkeley, focusing on probabilistic machine learning and Bayesian statistics applied to the analysis of single-cell transcriptomics data.
After having spent a few months as a consultant in these areas for a company called Immunai, I joined StatML to work with Chris on a project in collaboration with Novo Nordisk, at the intersection of causal inference and statistical machine learning for treating multimorbidity.
Outside academics, I enjoy history, running and I am trying to improve myself in gym and cooking.
After having spent a few months as a consultant in these areas for a company called Immunai, I joined StatML to work with Chris on a project in collaboration with Novo Nordisk, at the intersection of causal inference and statistical machine learning for treating multimorbidity.
Outside academics, I enjoy history, running and I am trying to improve myself in gym and cooking.
Sahra Ghalebikesabi
I am a second year StatML CDT student supervised by Chris Holmes. Currently I am working on handling model misspecification under synthetic data generation. My PhD is funded by Novartis where I am part of the IL-17 team at the BDI.
Samvida Venkatesh
I'm Samvida, a DPhil student in the Genomic Medicine and Statistics CDT based out of the Wellcome Centre for Human Genetics. I am co-supervised by Cecilia Lindgren at the Big Data Institute and Chris Holmes. My primary interest is in the genetics of multivariate trajectories and its applications in disease prediction. I work with both electronic healthcare records in the UK Biobank as well as multi-omics data from patient cell lines.
Xilin Jiang
I am a final year DPhil working on the impact of on disease risk, using various types of information available. Most of my previous work focused around estimating genetic risk effect accounting for multiple types of biases in survival analysis. Recently I became interesting in predicting disease risk (as a collaborative task) using external information including clinical classification of disease (ICD-10) and age.
During the weekend I work as a consultant to Gates Foundation and Chinese CDC, though little has happened for the past few months. Before the DPhil I worked on neural imaging modelling. (structure MRI and functional MRI). I did my undergraduate in Fudan University.
During the weekend I work as a consultant to Gates Foundation and Chinese CDC, though little has happened for the past few months. Before the DPhil I worked on neural imaging modelling. (structure MRI and functional MRI). I did my undergraduate in Fudan University.
George Nicholson
Alumni
Adaikalavan Ramasamy
Went on to:
A-STAR
Aimee Taylor
Went on to:
Harvard
Ajay Jasra
Went on to:
KAUST
Alexander Camuto
Went on to:
Alexandre Pintore
Went on to:
Citadel Securites
Anthony Lee
Went on to:
Bristol University
Avi Feller
Went on to:
UC Berkeley
Brieuc Lehmann
Went on to:
UCL
Chris Gamble
Went on to:
Google DeepMind
Chris Yau
Went on to:
Manchester University
Edwin Fong
Went on to:
Novo Nordisk
Eleni Giannoulatou
Went on to:
UNSW
James Watson
Went on to:
MORU
Louis Aslett
Went on to:
Durham University
Matthew Willetts
Went on to:
UCL
Mattias Rantalainen
Went on to:
Karolinska Institute
Maxine Mackintosh
Went on to:
Genomics England
Pedro Esperança
Went on to:
Huawei research
Peter Kecskemethy
Went on to:
Kheiron Medical
Quin Wills
Went on to:
Ochre Bio
Remi Bardenet
Went on to:
CNRS
Simon Lyddon
Went on to:
G-research
Tom Chittenden
Went on to:
Genuity Science
Tristan Grey-Davies
Went on to:
Marshall Wace
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