Towards an adaptive encoding for evolutionary data clustering. - Cameron Shand; Richard Allmendinger 001; Julia Handl; John Keane (GECCO, 2018)

Evolving controllably difficult datasets for clustering. - Cameron Shand; Richard Allmendinger 001; Julia Handl; Andrew M. Webb; John Keane (GECCO, 2019)

Evolutionary algorithms in clustering: challenging problem generation and search space adaptation. - Cameron Shand (2020)

pySuStaIn: A Python implementation of the Subtype and Stage Inference algorithm. - Leon M. Aksman; Peter A. Wijeratne; Neil P. Oxtoby; Arman Eshaghi; Cameron Shand; André Altmann; Daniel C. Alexander; Alexandra L. Young (SoftwareX, 2021)

Targeted Screening for Alzheimer's Disease Clinical Trials Using Data-Driven Disease Progression Models. - Neil P. Oxtoby; Cameron Shand; David M. Cash; Daniel C. Alexander; Frederik Barkhof (Frontiers Artif. Intell., 2022)

HAWKS: Evolving Challenging Benchmark Sets for Cluster Analysis. - Cameron Shand; Richard Allmendinger 001; Julia Handl; Andrew M. Webb; John Keane (IEEE Trans. Evol. Comput., 2022)

Artificial Intelligence for Dementia Research Methods Optimization. - Magda Bucholc; Charlotte James; Ahmad Al Khleifat; AmanPreet Badhwar; Natasha Clarke; Amir Dehsarvi; Christopher R. Madan; Sarah J. Marzi; Cameron Shand; Brian M. Schilder; Stefano Tamburin; Hanz M. Tantiangco; et al. (CoRR, 2023)

Bayesian inference of a new Mallows model for characterising symptom sequences applied in primary progressive aphasia. - Beatrice Taylor; Cameron Shand; Chris J. D. Hardy; Neil Oxtoby (CoRR, 2023)