Cole Johnston, PhD
Data science | Time-series analysis | Probabilistic modeling | Statistics | Machine learning
Convection is runaway buoyancy. Machine learning is runaway statistics.
Hi there! I’m a data science / astrophysics researcher with a decade of experience in exploring our Universe through the lens of data. I hold a PhD in Astrophysics from KU Leuven and have been fortunate enough to work as a postdoctoral researcher at Radboud University in the Netherlands (time series data science), the Max Planck Institute for Astrophysics in Garching, Germany (data science / signal processing), and I am currently an independent Newton International Fellow with the Royal Society at the University of Surrey in the UK (machine learning time series models).
I really enjoy working at the intersection of several fields - which is why my research involves integrating statistics, machine learning, and probabilistic modelling to understand different problems in astrophysics. In general, this lets me play around with complex, large-scale, and multi-dimensional datasets to uncover hidden patterns and make high-precision inferences. My work spans a range of methods, from developing bespoke models for astronomical signals to creating efficient data pipelines that manage vast quantities of observational data.
Outside of work, I can often be found hiking up mountains or cycling up hills.