Marcus Haywood-Alexander

According to our database, Marcus Haywood-Alexander authored at least 7 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Machine Learning and statistical classification of CRISPR-Cas12a diagnostic assays.

Nathan Khosla, Jake M. Lesinski, Marcus Haywood-Alexander, Andrew J. deMello, Daniel A. Richards

CoRR, January, 2025

2024

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

Marcus Haywood-Alexander, Giacomo Arcieri, Antonios Kamariotis, Eleni N. Chatzi

CoRR, 2024

2023

A Bayesian Method for Material Identification of Composite Plates via Dispersion Curves.

Marcus Haywood-Alexander, Nikolaos Dervilis, Keith Worden, Robin S. Mills, Purim Ladpli, Timothy J. Rogers

Sensors, 2023

Discussing the Spectra of Physics-Enhanced Machine Learning via a Survey on Structural Mechanics Applications.

Marcus Haywood-Alexander, Wei Liu, Kiran Bacsa, Zhilu Lai, Eleni N. Chatzi

CoRR, 2023

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

Marcus Haywood-Alexander, Robin S. Mills, Max D. Champneys, Matthew R. Jones, Matthew S. Bonney, David J. Wagg, Timothy J. Rogers

CoRR, 2023

Better Together: Using Multi-task Learning to Improve Feature Selection within Structural Datasets.

S. C. Bee, Evangelos Papatheou, Marcus Haywood-Alexander, Robin S. Mills, Lawrence A. Bull, Keith Worden, Nikolaos Dervilis

CoRR, 2023

2021

Structured Machine Learning Tools for Modelling Characteristics of Guided Waves.

Marcus Haywood-Alexander, Nikolaos Dervilis, Keith Worden, Elizabeth J. Cross, Robin S. Mills, Timothy J. Rogers

CoRR, 2021