About

Hi there — a waving hello.

I make biological dynamics computationally tractable

I am a computational systems biologist interested in how molecular networks change over time and in response to perturbation. My work focuses on signalling dynamics, cancer systems biology, multi-omics measurements and pharmacological processes.

Mathematical modelling is central to that work. I translate a biological question into an explicit quantitative representation, implement its ODE or PDE dynamics, and use numerical optimization, Bayesian inference and sensitivity analysis to connect model behaviour with measurements. Projects such as PhosKinTime, PhosCrosstalk and the tirzepatide PBPK model show different parts of that trajectory.

Reproducibility is part of the method

A model is most useful when its assumptions and computational path can be inspected. I therefore develop packages, documented workflows and interoperable model outputs alongside the analysis itself. This includes scientific Python, JAX numerical computing, SBML/PEtab model exchange, and containerized Nextflow workflows.

My longer-term direction is to combine interpretable mechanistic models with uncertainty-aware inference and multi-omics data, contributing quantitative methods toward precision medicine without overstating their current clinical scope.

Beyond research, I support open scientific exchange through BioBaes, a community initiative for people working across biology and data.

Beyond research

I also keep a personal photography gallery and can be contacted through the links in the site header.

Collaboration

I am particularly interested in collaborations involving longitudinal multi-omics, mechanistic disease models, signalling-network inference and reproducible scientific computing—especially where explicit models can connect molecular measurements to dynamic treatment response. If those questions overlap with your work, you can reach me by email, LinkedIn, or through my public GitHub profile.