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About Caitlin
Dr Caitlin Owen serves as a Postdoctoral Fellow in the Department of Information Science within the School of Computing at the University of Otago. She completed her academic training entirely at the University of Otago, obtaining a Bachelor of Science degree majoring in information science and computer science in 2014, a Master of Business Data Science with Distinction in 2016, and a PhD in 2021. Her doctoral dissertation, "Error Decomposition of Evolutionary Machine Learning," was recognized with the Otago Business School Exceptional PhD Thesis award. Owen's research interests encompass evolutionary computation, error decomposition, algorithm analysis and refinement, data augmentation, feature construction, feature selection, and the assessment of code quality on community question-answering platforms such as Stack Overflow.
She has made notable contributions through publications in high-impact venues. Among her most cited works is "A baseline model for software effort estimation" published in ACM Transactions on Software Engineering and Methodology in 2015, with 142 citations. Other key papers include "Examining the 'best of both worlds' of grammatical evolution" (GECCO 2015, 52 citations), "Understanding Stack Overflow code quality: A recommendation of caution" (Science of Computer Programming, 2020, 49 citations), "Using decomposed error for reproducing implicit understanding of algorithms" (Evolutionary Computation, 2024), "Characterising the double descent of symbolic regression" (GECCO 2024), and "Comparing blood biochemistry and haematology normal ranges of Chinook salmon from different production systems" (Aquaculture, 2025). In 2025, Owen received the Mana Tūāpapa Future Leader Fellowship from the Royal Society Te Apārangi to develop a transparent and energy-efficient automated machine learning system. Her work has amassed over 400 citations on Google Scholar, underscoring her impact in the field.
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