A hybrid talk by Dr Jack Atkinson, hosted by Leeds Institute for Data Analytics' (LIDA) Scientific Machine Learning (SciML) group.
Join us in person or online (MS Teams).
Abstract:
In the last decade, machine learning (ML) and deep learning (DL) techniques have revolutionised many fields within science, industry, and beyond. Researchers across domains are increasingly seeking to combine ML with numerical modelling to advance research. This typically brings about the challenge of programming language interoperation. PyTorch (Paszke et al., 2019) is a popular framework for designing and training ML/DL models whilst Fortran remains a language of choice for many high-performance computing (HPC) scientific models. The FTorch library provides an easy-to-use, performant, cross-platform method for coupling the two, allowing users to call PyTorch models from Fortran.
Bio:
Dr Jack Atkinson is a senior research software engineer in the Institute of Computing for Climate Science at the University of Cambridge. Prior to this he studied in the Engineering Department at Cambridge University investigating thermals and tropical cyclones, in the Geography Department modelling volcanic plumes, and as a Radiation Belt Scientist at the British Antarctic Survey. Jack's main interests are in geophysical fluid mechanics, specifically of the atmosphere, ocean, and space, but he likes to keep an open mind.
