Dr Krishna Margadhamane Gokhale PhD, MSc

• PhD in Computer Science, University of Birmingham, 2024
• MSc in Advanced Computer Science, University of Birmingham, 2016
• BE in Computer Science and Engineering, Visvesvaraya Technological University, India, 2013

Krishna graduated in Computer Science and Engineering from Visvesvaraya Technological University, India, in 2013 and worked as a software engineer at Capgemini India, developing and integrating enterprise systems for energy and finance clients. He moved to the UK for an MSc in Advanced Computer Science at the University of Birmingham, where he also taught Java programming and algorithms to undergraduate students. 

In late 2016 he joined what is now the Department of Applied Health Sciences to support Health Informatics and Epidemiology research and built a prototype tool for automating data extraction from primary care records. That prototype became DExtER (Data Extraction for Epidemiological Research). He developed and validated it as a part of his PhD (part-time) in the School of Computer Science supervised by Professor Peter Tiňo and Professor Krish Nirantharakumar. His doctoral work set out methods for automating epidemiological study designs, and used repeated measurements and machine learning to improve cardiovascular risk prediction in people with type 2 diabetes. The DExtER methods paper, published in the European Journal of Epidemiology in 2021, won the University's Michael O'Rourke Prize for the best publication from a PhD. 

In 2022 the team's data work was recognised by Health Data Research UK with its Team of the Year award and a Hidden Talent award. Krishna became Senior Research Fellow in 2023, taking responsibility for the department's research software engineering function and its data licences with CPRD, IQVIA and Cegedim, and was awarded his PhD in 2024. 

Alongside his academic work, Krishna led the commercialisation of Dexter through University of Birmingham Enterprise and Innovate UK's ICURe programme, leading to the spin-out company Dexter AI Ltd in 2023 and serves as Director and Chief Technology Officer of the company. He was appointed Associate Professor of Digital Engineering and Health Informatics in 2026.

Teaching Programmes

Health Informatics technical induction and Dexter training programme for new researchers, PhD and MSc students (lead, since 2017)

Real-World Data and Evidence training short course for medical students and junior doctors (co-designer and tutor, 2025, 2026)

Methods and data support for MSc dissertations and doctoral projects using UK primary care databases

Invited talks

Training on automated real-world evidence research at Maastricht University (2018), MORU and the National Health Foundation, Thailand (2022), New York State Department of Health (2023), the University of Western Australia (2023), The Ministry of Health of Peru (2025) and in Sri Lanka through the NIHR DigiPaths programme (2025)

Krishna supervises doctoral research in health data engineering, clinical decision support and methods for electronic health records. Current PhD students:

• Nissy Abraham (lead supervisor) – a data model for research on UK maternity services data
• Kasthuriraajan Ratnasingam (lead supervisor) – evaluation and implementation of AI and traditional clinical decision support systems in electronic health records
• Sai Suhas Varik (co-supervisor) – an automated pipeline for external validation and recalibration of risk prediction models in secondary care 

He has also given methods and data support to more than 60 postgraduate researchers and MSc students working with CPRD-HES, THIN and IMRD data. 

He welcomes enquiries from prospective PhD students interested in health data engineering, real-world evidence methods, and AI for electronic health records. 

For a full list of available Doctoral Research opportunities, please visit our Doctoral Research programme listings.

Krishna's research sits between software engineering and epidemiology. He builds methods and platforms that make observational research on electronic health records faster and more reproducible, and that let clinicians and epidemiologists work with large datasets without specialist programming. 

Automating epidemiological study designs

Dexter encodes common study designs – cohort, matched cohort, case-control, nested case-control and cross-sectional – as executable software, so that the extraction step handles common sources of bias consistently. It runs on a common data model that harmonises UK primary care databases (CPRD Aurum and GOLD with HES linkage, IQVIA Medical Research Data, and THIN UK and Europe). The platform has more than 100 active users in the University and has supported research on diabetes and cardiometabolic disease, mental health, women's and maternal health, eye disease, long COVID, pharmacoepidemiology, and the evaluation of national guidance.

Hospital and maternity data

He is extending the Dexter approach beyond primary care to hospital and maternity data, where the unit of analysis is not always a single patient. With the West Midlands Secure Data Environment and NHS trusts in the region, his team is building a research-ready maternity data model that brings together records from systems such as BadgerNet and Epic, and is mapping acute care data from University Hospitals Birmingham. Earlier work with Shrewsbury and Telford Hospital NHS Trust, to help with clinical audit of maternity records so that every case can be reviewed rather than a sample.

Data-driven trials and medication safety

Dexter has been used to emulate trials in historical populations to estimate recruitment and sample size, work that supported the funding of the NIHR DaRe2THINK trial, and to identify eligible participants for the NIHR-funded RADIANT trial of cardiometabolic testing in women with previous gestational diabetes, on which he is co-investigator. His current work includes reusable pipelines for detecting medication safety signals in primary and hospital care data. 

AI and foundation models

Krishna was co-investigator on the NIHR OPTIMAL study and the UKRI AI Accelerate project, which produced SurvivEHR, a time-to-event foundation model for multiple long-term conditions trained on primary care records. He is now working on language-model tools that help clinicians turn a research question into a well-defined study protocol that runs on the platform, with researchers keeping control of design decisions. 

Global health

In the NIHR DigiPaths programme he leads the technical work packages on digitally integrated care pathways for people with multiple long-term conditions in Sri Lanka, including interoperability with FHIR and the OMOP common data model.

Selected funding

• NIHR Global Health Research: DigiPaths – digitally integrated care pathways for multiple long-term conditions in Sri Lanka (co-investigator, £3.9M, 2024–2029)
• NIHR Birmingham Biomedical Research Centre: Data, Diagnostics and Decision Tools theme (co-investigator, 2022–2027)
• Asthma + Lung UK: sickness absence and its cost associated with lung disease in the UK working-age population (co-investigator, 2026–2028)
• NIHR Research for Patient Benefit: RADIANT data-driven trial platform in primary care (co-investigator, £385k, 2022–2026)
• NIHR: OPTIMAL – AI-assisted management of complex multimorbidity (co-investigator, £2.5M, 2021–2025)
• UKRI: AI Accelerate – clinical prediction foundation models for multiple long-term conditions (co-investigator, £640k, 2023–2025)
• Innovate UK ICURe Explore and Exploit: commercialisation of Dexter AI Ltd (principal investigator, 2023–2026)  

• Member, School Research Committee, School of Health Sciences, representing the Health Informatics and Multimorbidity team, with responsibility for research dissemination (2026–present)
• Director and Chief Technology Officer, Dexter AI Ltd, a University of Birmingham spin-out (2023–present)
• Co-Director, Dexter Operating Division, University of Birmingham Enterprise (2022–2026)
• Co-Investigator, Data, Diagnostics and Decision Tools theme, NIHR Birmingham Biomedical Research Centre 

Awards

• Michael O'Rourke Prize for the best publication from a PhD, University of Birmingham (2022)
• Team of the Year, Health Data Research UK (2022)
• Hidden Talent award – support for data, Health Data Research UK (2022)

Former posts

• Senior Project Manager, University of Birmingham (2023–2026)
• Research Fellow, University of Birmingham (2019–2023)
• Research Associate, University of Birmingham (2016–2019)
• Software Engineer, Capgemini India (2013–2014)