activity
20212025
most citedStructured Machine Learning Tools for Modelling Characteristics of Guided Waves

25 citations · 27 across the 3 of their papers we have counts for

collaborators

5 papers

q-bio.QM2025

Machine Learning and statistical classification of CRISPR-Cas12a diagnostic assays

Nathan Khosla, Jake M. Lesinski, Marcus Haywood-Alexander +2

CRISPR-based diagnostics have gained increasing attention as biosensing tools able to address limitations in contemporary molecular diagnostic tests. To maximise the performance of…

physics.comp-ph20242 cited

Response Estimation and System Identification of Dynamical Systems via Physics-Informed Neural Networks

Marcus Haywood-Alexander, Giacomo Arcieri, Antonios Kamariotis +1

The accurate modelling of structural dynamics is crucial across numerous engineering applications, such as Structural Health Monitoring (SHM), seismic analysis, and vibration contr…

eess.SY2023

Full-scale modal testing of a Hawk T1A aircraft for benchmarking vibration-based methods

Marcus Haywood-Alexander, Robin S. Mills, Max D. Champneys +4

Research developments for structural dynamics in the fields of design, system identification and structural health monitoring (SHM) have dramatically expanded the bounds of what ca…

cs.LG2023

Discussing the Spectrum of Physics-Enhanced Machine Learning; a Survey on Structural Mechanics Applications

Marcus Haywood-Alexander, Wei Liu, Kiran Bacsa +2

The intersection of physics and machine learning has given rise to the physics-enhanced machine learning (PEML) paradigm, aiming to improve the capabilities and reduce the individu…

stat.ML202125 cited

Structured Machine Learning Tools for Modelling Characteristics of Guided Waves

Marcus Haywood-Alexander, Nikolaos Dervilis, Keith Worden +3

The use of ultrasonic guided waves to probe the materials/structures for damage continues to increase in popularity for non-destructive evaluation (NDE) and structural health monit…