Soumya Banerjee
Assistant Research Professor
University of Cambridge
Summary
I am an Assistant Research Professor at the University of Cambridge working on explainable and trustworthy AI with applications in healthcare and computational biology. My work spans machine learning, federated and privacy-preserving analysis, complex systems, and reproducible research. I teach and supervise across undergraduate and postgraduate programmes and develop openly available teaching materials.
Contact
- Email: neel.soumya@gmail.com
- Website: Personal site
- Google Scholar: View profile
- GitHub: neelsoumya
- Teaching materials
- Download full CV (PDF)
Research interests
- Explainable & trustworthy AI
- Machine learning for healthcare and electronic health records
- Federated & privacy-preserving analysis (DataSHIELD)
- Computational & systems biology
- Complex systems, multi-scale simulation
- Reproducible research and scientific software
Recent positions
- Assistant Research Professor, University of Cambridge (2025–Present)
- Explainable AI techniques applied to healthcare; teaching and supervision.
- Senior Research Fellow & Affiliated Lecturer, University of Cambridge (2022–Present)
- Explainable AI techniques applied to healthcare; teaching and supervision.
- Postdoctoral Researcher, University of Cambridge (2019–2022)
- ML & data science on electronic health records; published in Nature Partner Journal Schizophrenia.
- Postdoctoral Researcher, University of Oxford (2016–2018)
- Researcher, CSIRO, Australia (2015–2016)
- Postdoctoral Research Fellow, Harvard Medical School & Broad Institute (2014–2015)
- Postdoctoral Research Fellow, Max Planck Institute for Molecular Physiology (2013–2014)
Education
- PhD in Computer Science, University of New Mexico, USA (2013)
- B.E. (Computer Science) with Distinction, Nagpur University, India (2003)
Teaching & supervision
Fellow of the Higher Education Academy (Advance HE). I teach introductory machine learning, reproducible research, and data visualisation. I have supervised MPhil students and PhD students and developed openly available course materials (links above).
Teaching portfolio
Below is a short teaching portfolio video and my teaching statement. If the embed does not load, open the video on YouTube.
Open teaching portfolio video on YouTube
If you would like a printable teaching statement, please contact me via email.
Mentoring
I take great pleasure in mentoring students and helping them develop their research and professional skills. Below is a mentoring perspective video where I share insights on working with students.
Selected publications
- Banerjee, S., Alsop, P., Jones, L., Cardinal, R. (2022). Patient and public involvement to build trust in artificial intelligence: a framework, tools and case studies. Patterns, 3(6):100506.
- Banerjee, S., Lio, P., Jones, P., Cardinal, R. (2021). A class-contrastive human-interpretable machine learning approach to predict mortality in severe mental illness. Nature Partner Journal Schizophrenia, 7:60.
- Aschenbrenner, D., Quaranta, M., Banerjee, S., et al. (2020). Deconvolution of monocyte responses in inflammatory bowel disease. Gut.
- Banerjee, S., Chapman, S.J. (2018). Influence of correlated antigen presentation on T cell negative selection in the thymus. Journal of the Royal Society Interface, 15(148):20180311.
- Mallick, H., Franzosa, E., McIver, L., Banerjee, S., et al. (2019). Predictive metabolomic profiling of microbial communities. Nature Communications, 10:3136.
For a complete publication list, see my Google Scholar profile.
Research statement
Watch my research statement video below. If the embed does not load, click the link to open the video on YouTube.
Research statement for AI applied to healthcare
Watch my research statement for AI applied to healthcare below. If the embed does not load, click the link to open the video on YouTube.
Open research statement for AI applied to healthcare on YouTube
Skills & tools
- Programming: Python, R, MATLAB, UNIX shell, C/C++, Perl, Haskell
- Databases: MS SQL Server, Sybase
- Image analysis: ImageJ, CellProfiler
- R packages: dsSurvival, dsSurvivalClient
Grants & invited talks (selected)
- OpenAI Researcher Access Program (API credits), Apr 2024
- AI@CAM Pilot Grants, Co-investigator, £150,000, Feb 2024
- Invited talk: Responsible AI and involving patients in AI model building, Nokia Bell Labs, Cambridge (Feb 2025)