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Caitlin Owen 2022 imagePostdoctoral Fellow

Room 3.30, Otago Business School
Tel +64 3 479 8410

Dr Caitlin Owen is a Postdoctoral Fellow in the Department of Information Science.

She received a Bachelor of Science degree majoring in information science and computer science in 2014 and a Master of Business Data Science degree (with Distinction) in 2016 from the University of Otago. She also completed a PhD degree (Error Decomposition of Evolutionary Machine Learning) in 2021 from the University of Otago, receiving a Business School Exceptional PhD Thesis award.

Her current research interests include evolutionary computation, error decomposition, algorithm analysis and refinement, data augmentation, feature construction, feature selection and CQA platform code quality.


Owen, C. A., Dick, G., & Whigham, P. A. (2023). Using decomposed error for reproducing implicit understanding of algorithms. Evolutionary Computation. Advance online publication. doi: 10.1162/evco_a_00321 Journal - Research Article

Owen, C. A., Dick, G., & Whigham, P. A. (2022). Towards explainable AutoML using error decomposition. Advances in artificial intelligence: Lecture notes in artificial intelligence (Vol. 13728). (pp. 177-190). Cham, Switzerland: Springer. doi: 10.1007/978-3-031-22695-3_32 Conference Contribution - Published proceedings: Full paper

Owen, C. A., Dick, G., & Whigham, P. A. (2022). Standardization and data augmentation in genetic programming. IEEE Transactions on Evolutionary Computation, 26(6), 1596-1608. doi: 10.1109/TEVC.2022.3160414 Journal - Research Article

Owen, P. D., & Owen, C. A. (2022). Simulation evidence on Herfindahl-Hirschman measures of competitive balance in professional sports leagues. Journal of the Operational Research Society, 73(2), 285-300. doi: 10.1080/01605682.2020.1835449 Journal - Research Article

Owen, C. A. (2021). Error decomposition of evolutionary machine learning (PhD). University of Otago, Dunedin, New Zealand. Retrieved from Awarded Doctoral Degree

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