Data Science and AI
AI/ML data scientist with a PhD and 15+ years turning large, heterogeneous biological and biomedical data into models, tools, and decisions — pairing deep statistical foundations with hands-on modern AI engineering.
Data Science
Statistical rigor, from study design to deployed models.
Bayesian Inference & Optimization
Optimization, inference, and decision-making under uncertainty — building principled frameworks that turn noisy, incomplete data into defensible decisions.
Simulation & Study Design
Enrollment and accrual, disease progression (time-to-event), and statistical power simulations that support study design and feasibility assessment.
Survival & Multivariate Statistics
Survival / time-to-event modeling, multivariate and spatial statistics, and rigorous model validation and interpretation.
Genomics & Computational Biology
Population and comparative genomics, phylogenomics, and high-throughput pipelines integrating high-dimensional biological data at scale.
Selected Projects
Detailed work across clinical R&D and computational biology.
Bayesian Optimization for Clinical Study Design
A Bayesian optimization framework that optimizes clinical study design under uncertainty, developed as a decision-support tool and presented to senior R&D leadership.
Clinical Simulation Suite
A suite of simulation models — patient enrollment and accrual, disease progression (time-to-event), and statistical power — supporting study design and feasibility assessment.
Production R Packages & Shiny Apps
Two R packages and R Shiny applications with integrated LLM components, now in active use by clinical oncology statisticians.
Agentic LLM Workflows via MCP
Agentic pipelines built on the Model Context Protocol that expose simulation and analysis tools through natural-language interfaces for non-technical scientists.
Clinical Literature RAG & Knowledge Graphs
Knowledge-graph and retrieval-augmented generation pipelines for large-scale clinical-statistics literature mining and question answering.
Patient Digital-Twin Simulation
A digital-twin framework that models individual patient trajectories for trial monitoring and study design.
Genomics Pipelines & the GABI-I Database
High-throughput Python/R pipelines integrating genomic, multispectral imaging, and 3D micro-CT data, plus GABI-I — a large open-access database of heterogeneous biodiversity records. Underpinning work published in Science.
AI
Generative and agentic systems for scientific workflows.
Agentic AI & MCP
Agent frameworks and Model Context Protocol tool integrations that let scientists drive simulation and analysis through natural language.
RAG & Knowledge Graphs
Retrieval-augmented generation and knowledge-graph systems for mining and answering questions over large scientific corpora.
LLM-Integrated Tools
Embedding LLM components into production statistical software so domain experts get generative capability inside the tools they already trust.
AI Safety & Responsible Deployment
Evaluating and responsibly deploying emerging AI — LLMs, agent frameworks, automated analysis — within rigorous scientific workflows, including AI safety evaluation.
Skills & Tools
From raw data to deployed models.