Machine Learning for Cancer Evolution and Treatment Resistance

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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.

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Reinforcement Learning Framework for Tumor Dynamics

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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.

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BioModelAnalyzer Platform Development

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