Scholar
Katherine M. Collins
Google Scholar ID: 48ZphCEAAAAJ
Machine Learning PhD Student at the University of Cambridge
Citations & Impact
Citations
2,305
H-index
18
i10-index
23
Publications
20
Co-authors
19
list available
Publications
Resume (English only)
Academic Achievements
- Published multiple papers, including 'Building Machines that Learn and Think with People' (pre-print, under review), 'Evaluating Language Models for Mathematics through Interactions' (PNAS, 2024), 'Human Uncertainty in Concept-Based AI Systems' (AIES, 2023), 'Eliciting and learning with soft labels from every annotator' (AAAI HCOMP, 2022), and 'Structured, flexible, and robust: benchmarking and improving large language models towards more human-like behavior in out-of-distribution reasoning tasks' (CogSci, 2022), with one paper receiving a travel grant.
Research Experience
- Conducting PhD research at the Computational and Biological Learning (CBL) Lab at the University of Cambridge, also as a visiting student with Josh Tenenbaum and the Computational Cognitive Science Group at MIT; previously a part-time Student Researcher at Google DeepMind, working with Krishnamurthy (Dj) Dvijotham; a Student Fellow at the Leverhulme Centre for the Future of Intelligence (CFI), and a volunteer with the Human-Oriented Automated Theorem Proving project led by Sir Tim Gowers.
Education
- MPhil in Machine Learning and Machine Intelligence from the University of Cambridge, supervised by Adrian Weller MBE and Richard Turner; Bachelor of Science from MIT in Brain and Cognitive Sciences, with minors in Computer Science and Biomedical Engineering.
Background
- PhD student in Machine Learning; research interests include applied computational cognitive science and human-AI interaction, particularly from the perspective of cognitive science. She is particularly interested in the study and design of AI thought partners that meet our expectations and complement our limitations, with a focus on applications in biomedicine, mathematics, and education.
Miscellany
- Enjoys running and used to run competitively for MIT; founded the MITxHarvard Women in AI Group during her undergraduate studies; helped co-organize multiple workshops such as the NeurIPS 2024 Workshops on Behavioral Machine Learning and COGGRAPH at CogSci 2024.
