Faculty
Prof Sarah Amalia Teichmann FMedSci FRS
Professor of Stem Cell Medicine, Cambridge Stem Cell Institute/Department of Medicine, Clinical School, University of Cambridge
Prof Teichmann is a world-leading scientist who combines her expertise in computational and systems biology with single-cell biology, genomics and immunology. She applies her knowledge using novel approaches to answer questions fundamental to our understanding of biology and medicine. Prof Teichmann is an EMBO member and a Fellow of the Academy of Medical Sciences and Royal Society, as well as a Fellow of the International Society of Computational Biology.
Prof Ari Ercole
Consultant in anaesthesia and intensive care medicine and chief clinical information officer, Cambridge University Hospitals NHS Foundation Trust • Fellow in Clinical Medicine, Magdalene College, University of Cambridge • Affiliated Associate Professor, Department of Medicine, University of Cambridge
As well as being a practicing clinician, Dr Ercole has a background in data science and also holds a PhD in experimental physics from the University of Cambridge. He is an expert in deployment of digital technology, including AI, in clinical care.
Prof Stefan Scholtes
Dennis Gillings Professor of Health Management, Cambridge Judge Business School • Director of the Centre for Health Leadership & Enterprise
Professor Scholtes’s research focuses on developing innovative business models to address population health challenges. His work integrates AI into novel workflows, financial models, and organisational structures. His research is deeply rooted in practice and conducted in close collaboration with healthcare provider organisations in both the NHS and the USA.
Prof Eoin McKinney
Professor in the Department of Medicine at the University of Cambridge • Honorary consultant in nephrology and transplantation, Cambridge University Hospitals NHS Foundation Trust
Prof McKinney’s research explores the interface between immune responses to infection and those driving inflammatory pathology, applying machine learning methods to the integration of multi-omics data, building interpretable predictive models for rapid translation into clinical practice while informing underlying disease biology and identifying novel therapeutic strategies.
Dr Alexander Gimson
Consultant Transplant Hepatologist, Cambridge University Hospitals NHS Foundation Trust • Chair of the Care Advisory Group, Cambridgeshire & Peterborough Sustainability and Transformation Partnership
Dr Gimson led the national team which developed in a new organ allocation offering scheme whereby organs are offered to the person on a national waiting list who has the greatest calculated net life years gained from the particular donor organ.
He is running a project which aims to discover if an AI/machine learning model can beat existing models, to make that organ-offering even more equitable.
Prof Angela Wood
Professor of Health Data Science, University of Cambridge
Prof Wood‘s research interests are centred on the development and application of statistical methods for advancing epidemiological research. She has focused on developing statistical methodology for handling measurement error, using repeated measures of risk factors, missing data problems, multiple imputation, risk prediction and meta-analysis.
Prof Pietro Liò
Professor of Computational Biology in the Department of Computer Science at the University of Cambridge • Member of the Artificial Intelligence group of the Computer Laboratory
Professor Liò has PhDs in Complex Systems and Non Linear Dynamics, and in Theoretical Genetics. He is the author of over 400 papers. His specialties include bioinformatics algorithms, predictive models in personalised medicine, modeling comorbidity and aging, methods for combining multi-scale biological processes, statistics of multi omics and multi physics modelling of molecules-cell-tissue-organ interactions.
Prof José Miguel Hernández Lobato
Professor of Machine Learning, University of Cambridge
Prof Hernández-Lobato‘s research includes fundamental contributions across a broad range of machine learning subfields such as deep generative modeling, Bayesian neural networks, Gaussian processes, Markov chain Monte Carlo methods, information theory, etc. His work also focuses on the applications of these techniques in real-world problems such as molecular modeling, drug design or data compression.
Prof Namshik Han
Head of AI Research, Milner Therapeutics Institute, University of Cambridge • Professor of Quantum Information, Yonsei University • Co-Founder of CardiaTec Biosciences & KURE.ai
Professor Han is a computational drug discovery scientist with expertise in quantum computing, artificial intelligence, computational biology, and multi-omics. He currently leads AI Research at the Milner Therapeutics Institute and holds additional roles at the Cambridge Centre for AI in Medicine and the Cambridge Stem Cell Institute.
He also serves as Professor of Quantum Information and IBS Professor of Advanced Science Institute at Yonsei University. His research develops quantum-AI technologies to decode complex multi-modal biomedical datasets, enabling discovery of new disease pathways, mechanisms, and therapeutic targets.
Prof Qingyuan Zhao
University Assistant Professor in the Statistical Laboratory, Department of Pure Mathematics and Mathematical Statistics (DPMMS), University of Cambridge • Turing Fellow, Alan Turing Institute
Prof Zhao is interested in improving the quality and appraisal of statistical research, including new methodology and a better understanding of causal inference, novel study designs, sensitivity analysis, multiple testing, and selective inference.
His substantive research focuses on causal inference problems arising in genetics and epidemiology.
Prof Richard Peck
Honorary Professor of Pharmacology & Therapeutics, University of Liverpool
Professor Peck spent over 30 years as a clinical pharmacologist in the pharmaceutical industry and was Global head of Clinical Pharmacology at Roche for the last thirteen of these. Since retiring from Roche, he has been appointed Honorary Professor of Pharmacology & Therapeutics at the University of Liverpool.
His research interests include understanding and utilising variability in drug response to enable precision dosing; applying clinical pharmacology to enable the development of personalised/stratified medicines and the use of model-based drug development strategies.
Dr Adrian Weller
Director of Research in Machine Learning, University of Cambridge • Programme Director for Trust and Society, Leverhulme Centre for the Future of Intelligence • Turing Fellow, Alan Turing Institute
Dr Weller MBE is a Programme Director and Turing Fellow leading work on Safe and Ethical AI at The Alan Turing Institute, the UK national institute for data science and AI.
His interests span AI, its commercial applications and helping to ensure beneficial outcomes for society. He serves on several boards including the advisory board for the Government’s Centre for Data Ethics and Innovation. Previously, Adrian held senior roles in finance.
Dr Mohammad Lotfollahi
Faculty, Wellcome Sanger Institute • Associate Faculty, Cambridge Stem Cell Institute, University of Cambridge
Dr Lotfollahi’s research focuses on developing AI/ML algorithms for biomedical data, with a specific emphasis on single-cell technologies for diagnostics, therapeutics, and drug discovery
Dr Richard Milne
Research Professor, Kavli Centre for Ethics, Science and the Public • Research Leader, RAND Europe
Richard Milne is a social scientist whose work addresses social and ethical challenges associated with new science and technology and the relationship between science and the public, primarily in the domains of genomics and the development of data-driven medicine. He is based in the Kavli Centre for Ethics, Science, and the Public in the Faculty of Education and at RAND Europe.
Prof Sergio Bacallado de Lara
Associate Professor, Department of Pure Mathematics and Mathematical Statistics, University of Cambridge
Prof Bacallado is an expert on Bayesian analysis, nonparametric statistical methods, and the applications of deep learning to the physical and biological sciences. In particular, he has worked on statistical applications in the fields of molecular dynamics simulation, drug discovery, hu-man microbiome studies, adaptive clinical trials, and the analysis of PET imaging data.
Dr J William L Brown
Consultant Neurologist, Cambridge University Hospitals • Leader Cambridge Big Data in Multiple Sclerosis Group
Dr Brown’s research focuses on preventing disability in multiple sclerosis by identifying the right drug, for the right patient at the right time. He also runs phase II repair trials, MRI research and national projects to widen research participation and automate data extraction from hospital records.
Prof Anders Christian Hansen
Professor of Mathematics, University of Cambridge • Professor II, University of Oslo
Prof Hansen is a member of the Department of Applied Mathematics and Theoretical Physics and head of the Applied Functional and Harmonic Analysis research group. His current research interests include but are not limited to Functional Analysis (applied), operator/ Spectral Theory, Compressed Sensing, Mathematical Signal Processing, Sampling Theory, Compressed Sensing, Mathematical Signal Processing, Sampling Theory, Computational Harmonic Analysis, Inverse problems, Medical Imaging, Geometric Intergration, Numerical Analysis, C*- algebras.
Prof Florian Markowetz
Professor of Computational Oncology, University of Cambridge • Senior Groupleader, CRUK Cambridge Institute • Co-founder and director of Tailor Bio
Professor Markowetz is received a Royal Society Wolfson Research Merit Award and a CRUK Future Leader in Cancer Research prize. He holds degrees in Mathematics (Dipl. math.) and Philosophy (M.A.) from the University of Heidelberg and a Dr. rer. nat. in Computational Biology from Free University Berlin, for which he was awarded an Otto-Hahn Medal by the Max Planck Society.
He is a co-founder and director at Tailor Bio, a genomics start-up developing a pan-cancer precision medicine platform
Prof Niels Peek
Professor of Data Science and Healthcare Improvement, THIS Institute, University of Cambridge
Professor Peek has a global reputation for his work on data-driven informatics for healthcare improvement, health data science, clinical prediction models, and computerised decision support tools.
With a background in computer science and artificial intelligence, Niels was President of the Society for Artificial Intelligence in Medicine until 2017.
He also led the Greater Manchester Connected Health City, part of a £20 million government investment to establish a learning health system in the north of England.
Prof Anna Moore
UKRI Future Leaders Fellow • Assistant Professor in Child Psychiatry and Medical Informatics, University of Cambridge • Clinical Lead NIHR Young Peoples BioResource – D-CYPHR • Associate Director, Centre for Human Inspired AI (CHIA)
Professor Moore’s goal is to develop personalised, preventative clinical pathways for children’s mental health. She is approaching this by harnessing broad data types, including electronic health record, genetic, deep phenotyping and other data types relating to children and young people, and making it available for research purposes in a shared data environment called CADRE (Child and Adolescent Data REsource). It is the most comprehensive database relating to children that has been created to date, and includes over 350,000 linked longitudinal records relating to children and young people.
Dr Tom Callender
Assistant Research Professor (Clinical) and Honorary Consultant in Public Health Medicine, University of Cambridge
Tom is an assistant research professor (clinical) at the University of Cambridge and honorary consultant in public health medicine at Cambridge University Hospitals. Tom trained in medicine in Manchester, Oxford, and London before specialising in public health. Alongside his research, he contributes to screening policy in the UK as a member of the UK National Screening Committee Multi-Cancer Detection Task Group and Research and Methodology Group. His research interests span screening, simulation modelling, and AI in medicine. He is affiliated with CCAIM and has been deeply involved with creating AutoPrognosis 2.0.
Dr Alexandru Marcoci
Assistant Professor of Global Risk and Resilience, Institute for Technology and Humanity, University of Cambridge
Alex is a social scientist interested in understanding the long-term impacts of frontier AI systems on social and democratic processes and developing interventions to shape these impacts and mitigate extreme risks. He has expertise in both methodologies for futures thinking and policy interventions for AI risk management in real-world organisations. Alex has been a UKRI Policy Fellow in the Department for Science, Innovation and Technology.
Affiliated Faculty
Prof David Bentley
Professor of Biochemistry and Molecular Genetics • Co-Director of the RNA Bioscience Initiative (2016-2024) at the U. Colorado School of Medicine
Prof David Bentley (BA, PhD, FRS) previously held group leader positions at the Amgen Institute U. Toronto (1995-’98), and Cancer Research UK (1987-1995). Bentley’s research in mechanisms that control gene expression has focused on : 1) control of transcription by RNA polymerase II at the steps of elongation and termination of RNA chains and 2) integration of different steps in mRNA biogenesis through coupling mechanisms that coordinate transcription with co-transcriptional pre-mRNA maturation and chromatin modification. Bentley’s “mRNA factory” model which proposed that coupling works by direct binding of mRNA processing factors to the C-terminal domain of actively transcribing RNA polymerase II has stimulated an active area of research.
Prof Radek Bukowski
Director of Computational Health & Medicine Initiatives at the Texas Advanced Computing Center, University of Texas at Austin • Honorary Senior Visiting Fellow, University of Cambridge
Prof Bukowski is a doctor, academic physician, scientist and an inventor. He is most known for his works in the fields of computational medicine, preterm birth, maternal fetal, and neonatal mortality and morbidity and fetal growth abnormalities. His works have been published in New England Journal of Medicine and American Journal of Obstetrics and Gynecology. He is also the recipient of 2008 March of Dimes Award for his research in prematurity.
Dr Simpson Zhang
Affiliate Senior Economist • Senior Financial Economist, Office of the Comptroller of the Currency • Lecturer in the MS in Applied Economics program, Johns Hopkins University
Dr Simpson Zhang is a lecturer at Johns Hopkins in the MS in Applied Economics program. His research interests are multidisciplinary and include network science, information economics, banking theory, and machine learning.
He currently serves as a Senior Financial Economist at the Office of the Comptroller of the Currency in Washington, D.C. Prior to joining the OCC in 2018, he was a researcher at the Office of Financial Research in the U.S. Department of Treasury. He holds a PhD in Economics from UCLA.
His work with CCAIM involves analysing the rise of AI agents in future labor markets and the potential economic forces that will affect them.
