research

Selected research projects and open-source work in AI-driven engineering.

Research projects spanning formulation optimisation, interpretable modelling, scientific evidence extraction, clinical machine learning and battery intelligence. Where possible, I share code and reproducible research materials.

Adaptive Batch Optimisation

Active learning for dermal formulations using GPR, expected improvement and hypervolume contribution to adaptively balance performance and information gain.

Early Decision-Making for IVPT

Probabilistic forecasting from partial permeation trajectories to stop unpromising experiments early while accounting for uncertainty.

Domain-Constrained Symbolic Regression

Interpretable dynamic models of dermal drug release that embed domain constraints, support optimisation and expose scientifically meaningful relationships.

SkinMiner

LLM-powered mining of dermal formulation evidence. SSRN preprint available; under review at International Journal of Pharmaceutics.

PhD Research Hub

The umbrella repository connecting publications, code, datasets and reproducibility materials across my doctoral research programme.

Clinical Machine Learning

Reproducible workflows for assisted-reproduction data, including outcome definition, feature construction and patient-aware, time-aware validation.

Battery Intelligence

Data processing, computational algorithms and research software for battery intelligence at Surrey's Advanced Technology Institute.

SkinPhysio-Extract

Evidence-grounded extraction and provenance auditing of quantitative skin physiology data during a Jagiellonian research visit.

Open-source research

Selected repositories: PhD research code · SkinMiner · Academic website.

Browse all repositories · GitHub profile