TLDR. PhD in AI and Cancer Imaging at the Institute of Cancer Research; co-created OsiriXgrpc, a clinical AI plugin used at The Royal Marsden serving care for patients. Previously delivered a 30% volume uplift and £5M increase in GWP on motor new business in commercial ML at Ageas Insurance. 11 abstracts/papers across MICCAI, AAAI, ISMRM, MIDL. Now running an AI and data analytics consultancy.
I build AI systems across healthcare, insurance, and applied research. PhD in AI and Cancer Imaging from the Institute of Cancer Research, where I shipped a clinical AI platform now used at The Royal Marsden Hospital. Before research, I led ML-driven pricing at Ageas Insurance.
Now running an AI and data analytics consultancy taking projects from scoping through to production deployment.
- 🛠️ Building: End-to-end pricing engine for an insurance client, unifying technical (burn cost) and commercial (market price) models into a single optimiser pipeline.
- 🔬 Experimenting: Foundation-model adaptation for medical imaging - see
dinov2-small-medniston Hugging Face. - 📖 Reading: The Foundation Models Initiative by Stanford CRFM; Interpretable Machine Learning by Christoph Molnar; recent MICCAI proceedings.
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clinical AI plugin Used at The Royal Marsden Hospital |
GWP uplift · 30% new-business volume Motor new business at Ageas via ML-optimised pricing |
abstracts / papers MICCAI · AAAI · ISMRM · MIDL CRUK 4-Year PhD Studentship |
| Domain | Detail |
|---|---|
| Healthcare AI | Co-created OsiriXgrpc - a gRPC plugin for OsiriX that brings real-time AI inference into radiologists' DICOM workflows. Used at The Royal Marsden Hospital, serving care for patients. Funded by the MedTech SuperConnector and the Sarcoma Accelerator Consortium. |
| Commercial ML | Led ML pricing at Ageas - delivered a 30% volume uplift and £5M increase in GWP on motor new business |
| Research | 11 abstracts/papers (MICCAI, AAAI, ISMRM, MIDL). Cancer Research UK 4-Year PhD Studentship |
| Open source | Contributor to The Turing Way (2.1k★) and NL-Augmenter (788★) |
"...the Medical Computer Vision Practical Tim produced has been used by multiple medical student cohorts to better understand what goes on under the hood in a computer vision classifier. I strongly recommend him for the person he is and the expertise he holds."
Nicholas Fuggle · Associate Professor of Rheumatology · Co-organiser, Alan Turing Institute Clinical AI Interest Group
Removes the historical bottleneck for clinical AI translation: state-of-the-art models live in Python, but radiologists work in OsiriX. The plugin lets the two talk in real time, without forcing the clinical team to leave their viewing environment. Source & documentation: github.com/osirixgrpc/osirixgrpc · osirixgrpc.github.io.
Interactive medical-image classification with GradCAM explainability visualisations - upload an image, see the model's classification and the regions it attended to. Built around a DINOv2-small vision transformer fine-tuned on MedMNIST v2. MONAI-compatible, SafeTensors, Apache-2.0.
Used as teaching material for:
- The Clinical AI Summer School at The Alan Turing Institute - the Institute's hands-on training programme for clinicians.
- The clinical student cohort at the University of Southampton.
A direct, hands-on demonstration of explainable medical AI - the same principles I worked on during my PhD on explainable AI for soft-tissue sarcoma at the Institute of Cancer Research, distilled into a public artefact that clinicians can pick up in minutes.
A collection covering card data, multimodal embeddings, and three Gradio spaces for Slay the Spire (STS 1 + STS 2). Personal experiments testing retrieval, embeddings, clustering, and LLM-driven recommendation on a well-defined constrained domain.
| Type | Title | What |
|---|---|---|
| Space | Build Me a Deck | LLM-driven deck recommendation from playstyle description |
| Space | Synergy Inspector | Pairwise synergy modelling + custom card design assistant |
| Space | Archetype Map | Interactive UMAP map of every STS 1 + 2 card |
| Space | OPTCG Card Explorer | Semantic search over One Piece TCG cards |
| Datasets | +10 datasets | Card data and multimodal embeddings for STS 1 + 2 and OPTCG |
Follow @t22000t for updates.
Tech I use most (click to expand)
ML & Deep Learning
Medical Imaging & CV
Languages
Infra & Data
- OsiriXgrpc: Rapid Development and Deployment of State-of-the-Art AI for Clinical Practice - AAAI 2022 (AI2SE Workshop)
- Radiomics Using Disentangled Latent Features from Deep Representation Learning in Soft-Tissue Sarcoma - MIDL 2023
- Multimodal Fusion for Radiogenomics Classification of Brain Tumor - MICCAI 2021 (BraTS Workshop)
- Uncertainty Quantification using U-Net with Monte Carlo Dropout - MICCAI 2021 (QUBIQ Workshop)
- Test-Retest Repeatability of Data-Driven Radiomic Features from Deep Learning - ISMRM 2022
Full list (11 papers): see LinkedIn Publications.
Open to conversations about applied AI roles, consulting engagements, and research collaborations where data and experimentation drive real commercial outcomes at speed.