DR MARTIN CHAPMANSoftware Engineer | Researcher
London, UKComputer ScienceSoftware EngineeringDevOps

Martin
Chapman

Software Engineer | Researcher

I have experience leading AI, distributed ledger and data integration projects in healthcare and other domains. I combine this experience with practical skills in software engineering. Starting my career in academia provided me with strong research, people and presentation skills.

Selected Work

And related outputs
01

MESAMedical Entity Extraction with Schema Alignment

Working on the secure deployment of Large Language Model (LLM) technology that converts unstructured NHS clinical documents into analysable data at scale. This represents one of the largest deployments of this technology in the health service. Leading external trust deployment, and developing training, deployment and inference pipelines to support the work. Example models include GenoLlama (genomic biomarkers) and OncoLlama (cancer).

02

GeNotes chatImproving the accessibility and usability of genomic clinical guidelines for clinicians

Led on the development and deployment of a RAG-based chatbot that provides an interactive frontend to NHS online genomic notes for clinicians (GeNotes). Features a novel graph-based retrieval technique, automated lookup metadata generation, and advanced privacy-preserving techniques. Widely evaluated within the health service.

03

digitalmimic.aiUsing AI to understand how preventative interventions can improve the health of children in the UK and reduce winter pressures on the NHS

04

SODAImproving the lives of stroke survivors with data

Co-led the development of a dashboard to enable stroke patients to access their data, to support research into data-based interventions. Dashboard was co-designed with patients, houses a data model tailored to key stroke-patient vitals, and includes built-in validated questionnaire tooling. Rolled out to patients as a part of King's College London's and Guy's and St Thomas's South London Stroke Register (SLSR).

05

REFLECTWearable sensors for personalised decision support

Led on the exploration of how sensor data can be used to better support patients with cardiometabolic disorders. Worked with Metadvice Ltd., a global health technology company, to deliver additional wearables-based components for their cardiometabolic decision-support system (DSS), which has been rolled out across the UK.

Software01

reflectMiddleware for interacting with wearable devices

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06

PhenoflowStandardise and share computable disease definitions

Worked as a part of HDR UK's National Phenomics Resource team to construct the UK's first national repository of computable disease definitions (phenotypes). Led on the development of Phenoflow, software that standardises repository phenotypes as Common Workflow Language (CWL) workflows. Phenoflow definitions and infrastructure support a variety of use cases around the world.

Publications04

Generating Computable Phenotype Intersection Metadata Using The Phenoflow Library2025 · AMIA Joint Summits on Translational Science
M Chapman, L Rasmussen, J Pacheco, L Wiley and V Curcin
Connecting Computable Phenotypes With Multiple Health It Standards Using The Phenoflow Library2022 · AMIA Clinical Informatics Conference
M Chapman, L V Rasmussen, J A Pacheco and V Curcin
Phenoflow: A Microservice Architecture For Portable Workflow-Based Phenotype Definitions2021 · AMIA Joint Summits on Translational Science
M Chapman, L Rasmussen, J Pacheco and V Curcin
Using Computable Phenotypes In Point-Of-Care Clinical Trial Recruitment2021 · Digital Personalized Health and Medicine
M Chapman, J Domínguez, E Fairweather, B C Delaney and V Curcin

Software01

phenoflowStandardise and share computable disease definitions

Talks06

Phenoflow: An Architecture for FAIRer PhenotypesThe Northwestern University Clinical and Translational Sciences (NUCATS) Institute/Institute for Augmented Intelligence in Medicine (I.AIM)/Center for Health Information Partnerships (CHIP), Northwestern University, Chicago, 2025 Generating Computable Phenotype Intersection Metadata Using the Phenoflow LibraryAMIA Informatics Summit, Pittsburgh, 2025 (presented by Professor Vasa Curcin)Phenoflow: An Architecture for Computable PhenotypesApplying FAIR principles to computable phenotype libraries, ELIXIR All Hands, Amsterdam, 2022Phenoflow 2021Clinical Natural Language Processing Group, University of Edinburgh, 2021Phenoflow: A Microservice Architecture for Portable Workflow-based Phenotype DefinitionsAMIA Informatics Summit, 2021Using computable phenotypes in point of care clinical trial recruitmentMedical Informatics Europe (MIE), 2021

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07

CONSULTCollaborative Mobile Decision Support for Managing Multiple Morbidities

Worked as a part of an interdisciplinary team to research the feasibility of employing a decision-support system (DSS) to enable chronic disease self-management. Led the development of a set of microservices for the DSS to support wearables data collection and integration, AI reasoning and real-time data analysis. These services represent a key deliverable in the £1.3m UKRI EPSRC CONSULT project.

09

Learning ErrorsFacilitating Code Merging with User-Defined Abstractions

Involved in exploring how finite automata can be used to represent software error traces. Developed a mechanism to estimate model-checking bounds, and the project’s merge feature. Sponsored by Google.

Software01

learning-errorsAbstractly represent software error traces as finite automata.

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