Computational biology grounded in chemistry, modelling, and research software.

Profile

I am Xi Yang (Ian), AMRSC, a PhD student in computational biology at the University of Edinburgh. My current research focuses on characterising and mathematically modelling metabolic oscillations in single cells, especially using yeast time-lapse microscopy, stochastic simulation, and machine-learning representations of biological time series.

Before starting the PhD, I trained across medicinal and biological chemistry, bioinformatics, drug discovery, and computational modelling. That background shapes how I work: I care about biological mechanism, reproducible software, and models that can be tested against experimental data.

Research Direction

My current project asks whether simulation-trained models can learn useful representations of noisy experimental traces. Recent work uses SimCLR, synthetic telegraph-model trajectories, and downstream classifiers to transfer from stochastic simulations to real transcription-factor localisation data.

Longer term, I am interested in interpretable and useful machine-learning workflows for single-cell biology, early-stage drug discovery, and robust scientific software.

Timeline

2024 - 2028 · PhD, University of Edinburgh

Swain lab and Grima group. Metabolic oscillations, single-cell time series, stochastic modelling, and machine learning.

2023 - 2024 · MSc Bioinformatics, University of Edinburgh

Bioinformatics programming, algorithmic workflows, protein sequence tools, and computational biology projects.

2018 - 2023 · MChem Medicinal and Biological Chemistry

Chemistry, drug discovery, computational chemistry, and pharmaceutical process optimisation.