Bio
Professor Matthew Juniper is Professor of Thermofluid Dynamics at the University of Cambridge and is partially seconded to the Alan Turing Institute as PI on the project 'Adjoint-accelerated Programmable Inference for large PDEs'. Matthew obtained his PhD in 2001 from the Ecole Centrale Paris and joined the University of Cambridge in 2003. He is an Associate Editor of the Journal of Fluid Mechanics, PI of the UK Fluids Network, and a Fellow of the American Physical Society.
Research interests
Matthew works on problems that combine data-driven machine learning methods with classical scientific modelling. Usually this involves assimilating data into qualitatively-accurate physics-based models using techniques similar to those used to train Neural Networks, rendering them quantitatively-accurate. This requires less data than a neural network, is interpretable, and extrapolates to situations that share the same physics. Matthew works mainly in flow instability, Flow-MRI, and thermoacoustics.
Achievements and awards
In 2023, Matthew's work won best paper award at the Symposium on Thermoacoustics in Combustion (Zurich) and runner-up at the International Conference on Sound and Vibration (Prague). He has has held visiting fellowships/professorships at Ecole Central Lyon, the Institute for Advanced Studies at TU Munich, KTH/Nordita Stokholm, IIT Madras, and the Center for Turbulence Research Summer Program at Stanford University.