Daniel Pitchforth is a research associate in the dynamics group at the University of Sheffield. His research interests focus on the integration of physical knowledge within machine learners, directed toward answering a few favourite questions: How can we most effectively combine physics and data for a particular task? What benefits can physics-informed models provide over purely data/physics-based approaches? How can we reap such benefits with application to structural dynamics?

During his PhD, he developed physics-informed models for offshore structures, with a specific focus on wave loading prediction. Currently, his research role involves working with industrial partners to implement PIML on real-world engineering challenges. Throughout his research career, an enthusiasm has grown for Gaussian processes, Kernel design and Autoregressive modelling.