Key details
Dr Peter Soar
Senior Lecturer in Computer Science
Peter was awarded a 1st class honours BSc in Mathematics from the 亚色影库 in 2013, going on to do part III of the Mathematical Tripos at the University of Cambridge, where he was awarded a Master of Advanced Study (MASt) in Mathematics and Statistics. Following this for two years he worked in industry in Data warehousing and visualisation for an internationally operating procurement company. Subsequently, Peter moved back into academia to work on his PhD Thesis titled ‘Integrating Structural Mechanics into Microstructure Solidification Modelling’ which was completed in 2021.
While Peter has teaching responsibilities and supervises students (from Undergraduate to PhD), much of his time is spent working on research projects within the Computational Science and Engineering Group (CSEG) in many topics. He is currently on the EPSRC prosperity partnership project ARCANE partnered with Rolls-Royce Ltd, Birmingham University and Oxford University looking at the impact of crystal anisotropy on the formation and properties of the microstructure of turbine blades. Outside of this Peter has a role in Knowledge exchange income, being Co-I on successful consultancy projects and KTPs.
Peter’s research is very interdisciplinary, incorporating elements of Computing, Mathematics, Statistics, Physics and practical experimental work for accurate numerical modelling and understanding of multi-Physics problems.
Responsibilities within the university
- Committee representative for Computing and Mathematical Sciences for the Early Career Researcher Network in Faculty of Engineering and Science.
- Supervisor for undergraduate and postgraduate projects in computer science, mathematics and data science.
- PhD supervisor to multiple students.
- Various teaching responsibilities.
Awards
- Winner in ‘Elevator Pitch’ Competition (UK Solidification Workshop, hosted by BCAST), 2022
- Inspiring Researcher Award (亚色影库), 2021
Recognition
Member of the Institute of Mathematics and its Applications (IMA)
Research / Scholarly interests
The core of Peter’s research pertains to the large-scale multi-physics simulations of microstructure solidification of metal alloys working with Professor Andrew Kao. His PhD topic was specifically on numerically modelling the structural mechanical behaviour during solidification the metal crystals which are present in (many) metal microstructures, which is often a source of defects in casting processes. This has since expanded to examining the physics driving formation of metal microstructure more generally due to my part in the EPSRC prosperity partnership project ARCANE partnered with Rolls-Royce Ltd, Birmingham University and Oxford University. This is interdisciplinary work at the intersection of Physics, Mathematics, Materials Science and High-Performance computing.
Relatively recently Peter has begun to engage with the use of Machine Learning methods in the field of materials mechanics in partnership with prof. Gianluca Tozzi from the School of Engineering, including the production of a prototype for a proof-of-concept Data-Driven Image Mechanics (D2IM) tool that allows displacements to be predicted directly from experimental imaging with knowledge of the loading conditions.
Key funded projects
- Co-I on PerformancePro-Net. Advanced AI for monitoring and prediction of performance in professional football players, 拢300K, 2025-2028
- Knowledge Base Supervisor for Knowledge Transfer Partnership with W盲rtsil盲 (10108115), 拢328K, 2025-2027
- Co-I on multiple beam times at the ESRF and Diamond Light Source since 2020
Recent publications
Article
Kaldre, Imants , Felcis, Valdemars, Krastins, Ivars, Soar, Peter , Tonry, Catherine E. H. , Kao, Andrew (2025), . Springer Minerals, Metals and Materials Society (TMS). In: , , , . Springer Minerals, Metals and Materials Society (TMS), JOM: The Journal of the Minerals, Metals and Materials Society (JOM) ISSN: 1047-4838 (Print), 1543-1851 (Online) (doi: https://doi.org/10.1007/s11837-025-07458-0) NB Item availability restricted.
Soar, Peter , Dall鈥橝ra, Enrico, Palanca, Marco, Tozzi, Gianluca (2024), . Elsevier. In: , , , . Elsevier, Extreme Mechanics Letters (EML), 71: 102202 2352-4316 (Online) (doi: https://doi.org/10.1016/j.eml.2024.102202).
Conference proceedings
Soar, Peter , Krastins, Ivars, Brown, Paul, Draper, Owen , Green, Nick , Kao, Andrew (2025), . Springer. In: , , In: Alexandra Anderson, Adrian S. Sabau, Chukwunwike Iloeje, Adamantia Lazou, Kayla M. Molnar (eds.), Materials Processing Fundamentals 2025: Thermodynamics and Rate Phenomena. Springer, Cham, Switzerland The Minerals, Metals & Materials Series (1st) . pp. 119-121 . ISBN: 9783031810527 ; 9783031810534ISSN: 2367-1696 (Print), (doi: https://doi.org/10.1007/978-3-031-81053-4_11) NB Item availability restricted.
Soar, Peter , Kao, Andrew, Djambazov, Georgi, Pericleous, Kyriacos A (2023), . IOP Publishing Ltd. In: , , , 16th International Conference on Modelling of Casting, Welding and Advanced Solidification Processes (MCWASP 2023). 18th - 23rd June 2023. Banff, Canada. IOP Publishing Ltd, Bristol, UK and Philadelphia, PA , 1281 (12045) (1st) . pp. 1-10 ISSN: 1757-8981 (Print), 1757-899X (Online) (doi: https://doi.org/10.1088/1757-899X/1281/1/012045).
Kao, A , Tonry, C, Soar, P, Krastins, I , Fan, X , Lee, PD , Pericleous, K (2023), . IOP Publishing Ltd. In: , , , IOP Conference Series: Materials Science and Engineering. IOP Publishing Ltd, , 1281 . pp. 12022 ISSN: 1757-8981 (Print), 1757-899X (Online) (doi: https://doi.org/10.1088/1757-899X/1281/1/012022).
Dataset
Soar, Peter , Palanca, Marco, Enrico, Dall'Ara, Tozzi, Gianluca (2024), . Peter Soar. In: , , , . Peter Soar, (doi: https://doi.org/10.6084/m9.figshare.25404220.v1).
Thesis
Soar, Peter and , (2021), . Unpublished. In: , , , . Unpublished, (doi: http://dx.doi.org/10.13140/RG.2.2.19089.44641).