Summary
Katriona Goldmann is a Research Data Scientist at the Alan Turing Institute with nine years’ experience applying machine learning, computer vision, and edge processing to automated biodiversity monitoring for insects, bats, and birds. Trained in astrophysics, biomedical engineering, and bioinformatics, she brings a rare multidisciplinary perspective that spans from modelling galaxies to integrating multi-omic clinical datasets. Her PhD and bioinformatics roles focused on translational research in autoimmune disease, producing practical tools such as an interactive Shiny app for large-scale transcriptomic visualisation. At the Turing she combines research engineering with deployable solutions for ecological sensing, emphasising open software and reproducible pipelines. Colleagues value her ability to translate complex scientific problems into robust, production-ready data systems and to collaborate across academic and engineering teams. She is open to collaborations that bridge open-source engineering, data science, and applied machine learning for environmental and biomedical challenges.
9 years of coding experience
1 year of employment as a software developer
Master of Physics, Astrophysics, First Class Honours, Master of Physics, Astrophysics, First Class Honours at The University of Edinburgh
Master of Biomedical Engineering, Biomedical/Medical Engineering, Distinction, Master of Biomedical Engineering, Biomedical/Medical Engineering, Distinction at University of Strathclyde
Doctor of Philosophy - PhD, Medical Statistics, Pass, Doctor of Philosophy - PhD, Medical Statistics, Pass at Queen Mary University of London
English, German