The Team

In preparation for this development award we have assembled a team of computer and data scientists, statisticians, epidemiologists and clinicians with skills and interests in data analysis and interpretation, to address how to apply artificial intelligence (AI) methodology to develop new insights into the detection and prevention of multimorbid conditions.

By establishing a group of experts in clinical medicine, biological sciences, epidemiology, computing sciences and statistics to bring a focus on inflammatory drivers of comorbidity, we expect this development work to demonstrate the feasibility of novel AI technologies to identify inflammation driven clustering of patient disease trajectories over a long time horizon.

Epidemiology and Clinical Medicine

Prof. Alex MacGregor

Prof. Alex MacGregor

Epidemiologist (NMS, UEA)

Prof. Alexander MacGregor
Professor of Genetic Epidemiology, Norwich Medical School, University of East Anglia
Email: a.macgregor@uea.ac.uk​
Professor of Genetic Epidemiology at UEA. He is a clinical rheumatologist with a research career that has focused on the epidemiology of chronic rheumatic diseases both from the perspective of aetiology and health services research. PI for the Norfolk Arthritis Register. Close involvement with a number of national data projects, including the National Joint Register, CPRD, ELSA and UK Biobank.

Prof. Chris Fox

Prof. Chris Fox

Clinical Researcher (NMS, UEA)

Prof. George Christopher Fox
Clinical Professor, Norwich Medical School, University of East Anglia
Email: chris.fox@uea.ac.uk
Professor of Clinical Psychiatry, led multiple NIHR programmes in co-morbidity intervention development. Expertise in applying data to clinical problems and working with AI to develop new clinical assessment applications. Mental health lead for MRC Gemini multimorbidity project. Experience of working with CPRD, Eclipse and large clinical trial data sets.

Prof. David Llewellyn

Prof. David Llewellyn

Epidemiologist (Exeter)

Prof. David Llewellyn
Professor of Clinical and Epidemiology and Digital Health, University of Exeter
Email: david.llewellyn@exeter.ac.uk​

Professor and Fellow at the Alan Turing Institute. Epidemiologist with expertise in evidence synthesis, data science and machine learning. Exeter Institute for Data Science and Artificial Intelligence Clinical Theme Lead and the Turing Exeter University Clinical Lead. Director of the DEMON Network, an international network for data science and AI applied to dementia research and healthcare

Prof. Ian Bruce

Prof. Ian Bruce

Epidemiologist

Professor of Rheumatology at the Centre for Musculoskeletal Research, University of Manchester
Email: ian.bruce@manchester.ac.uk​

Clinical and molecular epidemiologist. Director of the NIHR Manchester Biomedical Research Centre. Chief Investigator for the NIHR ImmuneMediated Inflammatory Disease BioResource and the the MRC-funded SLE Stratified Medicine Consortium. Research focus is on the association between inflammatory rheumatic diseases and premature cardiovascular disease and on contribution of metabolic syndrome.

Statistics

Prof. Elena Kulinskaya

Prof. Elena Kulinskaya

Professor in Statistics (Aviva Chair in Statistics), School Of Computing Sciences, University of East Anglia
Email: e.kulinskaya@uea.ac.uk
Professor, Aviva Chair in Statistics, Director of the Data Science and Statistics Laboratory, UEA.Strong research interests in statistical modelling for Big Data, in meta-analysis and research synthesis, and extensive experience of statistical modelling of electronic health records. Wide experience of statistical consulting in health, conservation, life and actuarial sciences and industry.

Prof. Lee Shepstone

Prof. Lee Shepstone

Professor of Medical Statistics, Norwich Medical School, University of East Anglia
Email: l.shepstone@uea.ac.uk​

Professor of Medical Statistics. Part of MRC Gemini multimorbidity project. Experience of working with CPRD, Eclipse and large clinical trial data sets

Prof. Berthold Lausen

Prof. Berthold Lausen

Professor of Statistics, Department of Mathematical Sciences, University of Essex
Email: blausen@essex.ac.uk​

Professor of Data Science, Head of Department, Mathematical Sciences, University of Essex. Past President of the International Federation of Classification Societies (IFCS) (2018-19), founding vice-president of the European Association for Data Science (EuADS) (2015-2018), former president of the GfKl Data Science Society (2013-19), and member of the committee of the British Classification Society (BCS). Expertise in ensemble methods for supervised learning (classification) and nonparametric methods based on maximally selected statistics.

Dr. Mizanur Khondoker

Dr. Mizanur Khondoker

Senior Lecturer in Medical Statistics, Norwich Medical School, University of East Anglia
Email: m.khondoker@uea.ac.uk​

Senior Lecturer in Medical Statistics, UEA. Expertise in machine learning, analysing high dimensional data, particularly those arising from routine electronic health records systems, and modern bioinformatics and genomics technologies. Leadings a multimorbidity research project using the UK Biobank cohort. Core interest in multimorbidity research and latent class trajectory analysis.

Dr. Alexandra Lewin

Dr. Alexandra Lewin

Associate Professor in Biostatistics, London School of Hygiene and Tropical Medicine
Email: alex.lewin@lshtm.ac.uk​

Associate Professor in Biostatistics, Department of Medical Statistics, London School of Hygiene and Tropical Medicine. Expertise in machine learning and integrated analyses of multiple -omics datasets in longitudinal studies. Wide-ranging expertise as epidemiology (including molecular), biostatistics, bioinformatics, and laboratory genomics.

Dr. Jack Dainty

Dr. Jack Dainty

Statistician and Data Analyst, (NMS, UEA)

Senior Research Associate in Epidemiology, University of East Anglia
Email: jack.dainty@uea.ac.uk​

Research statistician, data analyst and programmer with expertise in managing large datasets including UK Biobank, NJR and HES. He has specific expertise in nutritional epidemiology and bioinformatics.

Dr. Ilyas Bakbergenuly

Dr. Ilyas Bakbergenuly

Senior Research Associate, School Of Computing Sciences,University of East Anglia
Email: i.bakbergenuly@uea.ac.uk​

Senior Research Associate in statistics. Expertise in extraction and analysis of EHR, R and SQL programming, advanced statistical methods of survival analysis, life expectancy, meta-analysis.

Computer Science and Data Science

Prof. Anthony Bagnall

Prof. Anthony Bagnall

Professor of Computer Science, School Of Computing Sciences, University of East Anglia
Email: anthony.bagnall@uea.ac.uk
Professor of Computer Science, UEA. Expertise in novel algorithms for time series classification and clustering. Core developer for the scikit-learn compatible time series toolkit sktime, hosted by the Alan Turing Institute, and its Keras compatible sister package sktime-dl.

Prof. Vincent Moulton

Prof. Vincent Moulton

Professor in Computational Biology, School Of Computing Sciences, University of East Anglia
Email: v.moulton@uea.ac.uk​

Professor of Computing Science, UEA. Expertise in metagenomics methodology and for microbiome time-series analysis.

Dr. Wanqing Zhao

Dr. Wanqing Zhao

Lecturer in Computing Sciences, School Of Computing Sciences, University of East Anglia
Email: w.zhao2@uea.ac.uk​
Lecturer in Computing Science, UEA. Expertise in solid mathematics-based, low-complexity machine learning, optimisation and control algorithms, and their applications in diverse sectors by integrating with IoT, cloud computing and, app and web based development.

Dr. Min Hane Aung

Dr. Min Hane Aung

Lecturer in Computing Sciences, School Of Computing Sciences, University of East Anglia
Email: min.aung@uea.ac.uk​

Lecturer in Computing Science, UEA. Research interest in the advancement of machine recognition of human states and behavior in everyday settings draws upon a range of fields that include Ambient Intelligence, Machine Learning, Ubiquitous Computing, Effective Computing and Human Computer Interaction. Expertise in Artificial Neural Networks for survival analysis.

Dr. Tahmina Zebin

Dr. Tahmina Zebin

Lecturer, School of Computing Sciences, University of East Anglia

Email: t.zebin@uea.ac.uk

Lecturer in the School of Computing Sciences, UEA and is one of the academic leads for On-device and Explainable AI research. Her research expertise includes Advanced Video and Signal Processing, Explainable and Inclusive AI, Human Activity Recognition, Risk Prediction modelling using various statistical machine learning and deep learning techniques. Relevant expertise in Neural ODE Networks for multi-state survival analysis.

Dr. Sarah Bauermeister

Dr. Sarah Bauermeister

Senior Data and Science Manager
Email: sarah.bauermeister@psych.ox.ac.uk

Senior Data and Science Manager for Dementias Platform UK (DPUK), University of Oxford. Programme Lead for the Early Adversity and Dementia Programme; Steering Group Member for DEMON (The Deep Dementia Phenotyping Network); PI of an international collaboration for Covid-19 and mental health. Leads a programme of work across multi-modal data (clinical, imaging, genetic) focused on understanding multi-morbidities of disease outcomes such as Parkinson’s and Alzheimer’s Disease.

PPI representatives

Ron Brewer

Ron Brewer

Patient partner (NNUH)

Patient partner. Patient research ambassador for Norfolk and Norwich Hospital
Email: crockslea@aol.com​

Patient and public representative.Ron is a patient research ambassador and volunteer at the Norfolk and Norwich University Hospital (NNUH). Since retiring after 40 years as a research scientist he has participated in short and long term clinical trials at both the NNUH and the UEA. He advises local researchers on their projects from the point of view of a participant

Jane Scarfe

Jane Scarfe

Patient partner

Chair THE RiNG, Rheumatoid in Norfolk Group

Email: janescarfe@gmail.com

Jane is a recent Lead Governor at the Norfolk & Norwich University Hospital (NNUH) who has chaired the Norfolk arthritis support group THE RiNG for over 12 years. She is one of the lay consultees on the InflAIM project whose input has focused on prioritising its relevance and significance to patients.