Rigorous methodology meets practical engineering. From statistical modeling to interactive web tools.
My deepest expertise. Over a decade building spatial and spatio-temporal models for global health, environmental science, and genomics. I've produced 5×5km resolution maps of health outcomes across Africa and low- and middle-income countries, published in Nature, Nature Medicine, The Lancet, and the New England Journal of Medicine.
Whether you need to model disease prevalence across a continent, predict environmental change over time, or analyze spatially-resolved gene expression data, I bring methods grounded in decades of statistical theory to problems with real spatial and temporal structure.
From study design through model building to interpretation, I bring Ph.D.-level rigor to your data problems. Bayesian and frequentist methods, predictive modeling, and rigorous uncertainty quantification, all tailored to your domain.
I also build and deploy machine learning systems: predictive pipelines, classifiers, and clustering solutions designed for your specific data and production requirements.
Custom websites, web applications, and interactive platforms built with clean architecture and a focus on performance. I specialize in data-driven web tools that put complex information into users' hands, from educational platforms to analytical dashboards.
My approach emphasizes simplicity and longevity: I build with web standards and deploy on modern platforms, creating sites that are fast, accessible, and easy to maintain.
New ways of looking at data provide new insights from the data. I build bespoke interactive visualizations that let you and your team see patterns, explore relationships, and discover what your data is actually telling you.
From geographic heatmaps to network flow diagrams, I create tools that go far beyond standard charts: purpose-built visual instruments that make complex datasets explorable and understandable.
Complex systems, models, and data don't explain themselves. I turn them into things people can actually understand: interactive explainers, clear documentation, teaching materials, and presentations that meet your audience where they are.
This isn't about dumbing things down. It's about finding the right lens. I've explained spatio-temporal statistical models to public health ministries, taught Bayesian inference to undergraduates, and built interactive guides that make decentralized AI networks navigable. Whether your audience is a boardroom, a classroom, or a developer community, I make the complex genuinely clear.
Let's talk about what you need and how I can help.