Education
Bayesian modelling of inversion problems in human-AI interaction (preliminary title)
Professor Mark Steyvers
Computational modelling of human problem-solving abilities and alignment of AI systems with human cognition
Cognition-Inspired Heuristics Improve Machine-Learning Predictions in Multi-Attribute Multi-Alternative Choice
Professor Nick Chater
: Behavioral and Data Science (equivalent to )
Unifying models from computational cognitive science and machine learning
Cooperation does not improve selective and/or sustained attention
Dr. John Michael and Dr. Ross Goutcher
for the Best Single Honours Psychology Student (equivalent to )
for the Best Psychology Dissertation
Measuring cognitive abilities in online games
Research Experience
Conducted large-scale mixed methods study concerned with the prediction of online group communications which translate into real-world actions
Developed own project investigating algorithms for complex research appointment scheduling
Principal Investigator: Professor Adam Joinson
Execution and data analysis of experiments concerning face matching and concealed identity recognition
Principal Investigator: Dr. Ailsa E. Millen
Automated video analysis for discrimination learning in lumpfish
Principal Investigator: Dr. Jamie Murray
Publications
Steyvers, M., Tejeda, H., Kumar, A., Belem, C., Karny, S., Hu, X., Mayer, L. W., & Smyth, P. (2025). What large language models know and what people think they know. Nature Machine Intelligence. https://doi.org/10.1038/s42256-024-00976-7
Karny, S., Mayer, L. W., Ayoub, J., Song, M., Su, H., Tian, D., Moradi-Pari, E., & Steyvers, M. (2024). Learning with AI Assistance: A Path to Better Task Performance or Dependence? Proceedings of the ACM Collective Intelligence Conference, 10–17. https://doi.org/10.1145/3643562.3672610
Mayer, L. W., Bocheva, D., Hinds, J., Brown, O., Piwek, L., Ellis, D. (under Review) Waste not want not: Computational methods to maximise attendance in group research. Behavior Research Methods.