Machine Learning for Cancer Evolution and Treatment Resistance

I am developing predictive models for cancer evolution and treatment resistance at UCL Cancer Institute. My work focuses on improving therapy identification through advanced ML techniques and supporting clinical decision-making processes.

Reinforcement Learning Framework for Tumor Dynamics

Designed a reinforcement learning framework that models tumor evolutionary dynamics to predict treatment outcomes. The research incorporates spatial agent-based simulations with clonal dynamics and phylogenetic tree structures.

BioModelAnalyzer Platform Development

Leading engineering efforts on BioModelAnalyzer, fixing critical bugs, enhancing system reliability, and deploying cloud-integrated bioinformatics pipelines for computational biology research.