Catherine Higham

Dr. Catherine Higham is a Research Fellow in the School of Computing Science at the University of Glasgow, affiliated with Prof. Rod Murray-Smith's Inference, Dynamics and Interaction group. Her work focuses on applying machine learning and statistical methods to inverse problems in quantum optics and systems biology. Previously, she held roles as a Research Associate in the EU-funded TiMet project (2012–2015) and completed a Daphne Jackson Trust Fellowship (2006–2008) followed by a Lord Kelvin/Adam Smith PhD Scholarship (2008–2012) at Glasgow.

Education includes a Mathematics degree from the University of Oxford, an MBA from City University London (sponsored by Novaction), and a PhD in computational biology from the University of Glasgow under Prof. Darren Monckton. Her interdisciplinary research spans machine learning, statistical inference, high-performance computing, and collaborative work with experimental scientists.

Research interests emphasize developing algorithms for data-driven scientific understanding, particularly in quantum technologies and biomedical applications. Key contributions include Bayesian deep inversion, quantum annealing for neural networks, and parameter estimation in biological systems. She has also explored applications in single-pixel imaging and LiDAR optimization.

Scientific awards include the Daphne Jackson Trust Fellowship and Lord Kelvin/Adam Smith PhD Scholarship. Grants include EPSRC UK Quantum Technology Programme funding. Catherine's work bridges computational methods with real-world challenges in physics, biology, and linguistics, supported by collaborations across disciplines.