UCL’s Progression Of Neurodegenerative Disease (POND) group is developing new computational models and techniques for learning characteristic patterns of disease progression using large cross-sectional data sets. Our focus is currently on dementias, such as Alzheimer’s disease, but our techniques have wider application to other diseases and developmental processes.

We are considering a broad approach to modelling disease progression, starting with Hubert Fonteijn’s work in NeuroImage 2012 on event-based models, and also exploring the possibility of determining causal links between events. Events constitute biomarker abnormality, which includes image-based biomarkers such as regional atrophy in the brain, as well as biomarkers such as levels of abnormal proteins in cerebrospinal fluid.

All the while, we ensure clinical relevance in the models through collaboration with the Dementia Research Centre at UCL’s Institute of Neurology.

UCL POND started with an EPSRC-funded project (see our projects for more details) and are coordinators of the EuroPOND (a Horizon 2020 project) and E-DADS (EU JPND) consortia.

Research Vision

The Challenge

The global ageing population has placed neurodegenerative diseases among the biggest public health challenges of 21st century healthcare. It is vital to understand this spectrum of diseases on both mechanistic and phenotypic levels to elucidate differences and similarities that can inform diagnosis, prognosis, monitoring, therapy development, and treatment & care decisions.

The Vision

Our vision in the POND initiative at UCL is to provide new avenues for understanding the complexity of clinical phenotypes of multifactorial neurological diseases. Disentangling this complexity by identifying signatures of each disease is essential for meeting the challenge.

The Means

The platform upon which we will build the tools for achieving this vision is data-driven computational-and-statistical modelling, a set of powerful approaches with the ability to provide fine-grained and uniquely holistic pictures of neurological disease progression. Such emerging technologies will underpin support systems for clinical and drug-development applications, specifically by enabling precision medicine through differential diagnosis, patient staging, and personalised prognosis.

The Strategy

Our strategy for achieving impact within our vision requires a balance between model utility and complexity. Model utility is the end-game focus in order to impact disease management across the full spectrum from patients to medical health professionals and drug-development companies. Model complexity is unavoidable due to the nature of the disease signatures we seek, and requires methodological development, which is one of our group’s strengths.


Principal Investigators


Prof Danny Alexander

Principal Investigator


Dr Neil Oxtoby

Co-Leader, Co-Founder, UKRI Future Leaders Fellow

Guitar, Singing, Songwriting


Dr Peter Wijeratne (he/him)

MRC Skills Development Fellow

Research Associates/Fellows


Dr Arman Eshaghi M.D.

Senior Research Fellow


Dr Le Zhang

Research Fellow


Dr Cameron Shand

Research Fellow in Disease Progression Modelling and Machine Learning for Clinical Trials

Staying inside


Dr Eda Bilici Ozyigit

Research Fellow in Medical Informatics and Machine Learning


Dr Hanyi Chen

Senior Research Fellow

PhD Students


Nonie Alexander

PhD Student


An Zhao

PhD Student


Anna Schroder

PhD Student


Seymour Lopez

PhD Student


Will Scotton

PhD Student


Ms Zeena Shawa

MRes Student

Powerlifting, Art, Video Games


Beatrice Taylor

PhD Student


Isaac Llorente Saguer

PhD Student

Understanding & learning stuff, poka yoke


Liza Levitis

PhD Student




Eline Vinke

Visited Nov 2018 – Jan 2019

Riccardo Pascuzzo

Visited Nov 2016 – Jan 2017

Dr Esther Bron

Visited Sep 2015 – Dec 2015


Dr Alexandra Young

PhD (POND original), Postdoc => KCL Fellow (Sep 2019)

Dr Razvan-Valentin Marinescu

PhD student => Postdoc at CSAIL, MIT (Oct 2018)

Dr Nicholas Firth

Research Associate => Industry (Oct 2018)


Maura Bellio

PhD Student (defended May 2021) => Industry


Dr Leon Aksman

Research Associate => USC faculty (Nov 2020)

Dr Sara Garbarino

Research Associate => Research Fellow at Inria Sophia Antipolis (2018)


Kyriaki (Rica) Mengoudi

PhD student (defended March 2021) => Industry


Dr Daniele Ravi

Senior Research Associate => University of Hertfordshire faculty (Jan 2020)


Dr David Cash

Principal Research Fellow, UCL IoN

Prof Frederik Barkhof

Chair of Neuroradiology, UCL IoN

Dr Rimona Weil

Principal Research Fellow, Weill Lab, UCL IoN

Dr Joseph Jacob

Principal Research Fellow

Prof Zuzana Walker

Professor of Psychiatry of the Elderly, UCL Division of Psychiatry

Dr Jacob Vogel

Postdoctoral Fellow, PennLINC

Prof Olga Ciccarelli

Professor of Neurology, IoN

Dr Jon Huang

Research Scientist, Google

Recent Publications

Filter and view more publications here.

Four distinct trajectories of tau deposition identified in Alzheimer’s disease

Alzheimer’s disease (AD) is characterized by the spread of tau pathology throughout the cerebral cortex. This spreading pattern was …

Identifying multiple sclerosis subtypes using unsupervised machine learning and MRI data

Multiple sclerosis (MS) can be divided into four phenotypes based on clinical evolution. The pathophysiological boundaries of these …

Sequence of clinical and neurodegeneration events in Parkinson's disease progression



Data-driven models for Progression Of Neurological Disease

E-DADS: Early Detection of Alzheimer’s Disease Subtypes

Data-driven models for Progression Of Neurological Disease

Memory Clinic Patient Management Tools

Analysing over 20 years of clinical and imaging data from the Essex Memory Clinic for differential diagnosis and prognosis

Computational models for clinical trial design in Huntington’s disease

Pete’s MRC Skills Development Fellowship aims to change the way disease modifying therapies in Huntington’s Disease are developed

I-AIM: Individualised Artificial Intelligence for Medicine

Neil’s UKRI Future Leaders Fellowship

Learning personalised trajectories in Huntington’s disease through computational models of disease progression

Advancing our recent developments in computational modelling of Huntington’s disease (HD) to establish a staging system that can both stratify patients and estimate rate of progression and time between key pathological event

Past Projects

See here for a list of our past projects