Scholar
Lea Frermann
Google Scholar ID: y3l6y4IAAAAJ
Computing and Information Systems, The University of Melbourne
Citations & Impact
Citations
835
H-index
15
i10-index
23
Publications
20
Co-authors
6
list available
Contact
Publications
Resume (English only)
Research Experience
- [{'Position': 'Senior Lecturer', 'Institution': 'University of Melbourne', 'Time': '2023-Present'}, {'Position': 'Lecturer', 'Institution': 'University of Melbourne', 'Time': '2019-2023'}, {'Position': 'Postdoc / Applied Scientist', 'Institution': 'Amazon Core AI (Berlin)', 'Time': '2018-2019'}, {'Position': 'Research Associate', 'Institution': 'ILCC, University of Edinburgh', 'Collaborators': 'Mirella Lapata, Shay Cohen', 'Time': '2017-2018'}, {'Position': 'Visiting Scholar', 'Institution': 'Stanford University Language and Cognition Lab', 'Host': 'Michael Frank', 'Time': '2017'}, {'Position': 'Machine Learning Intern', 'Institution': 'Amazon Berlin', 'Time': '2016 (3 months)'}, {'Position': 'Erasmus Mundus Research Exchange Student', 'Institution': 'NTU Singapore', 'Collaborator': 'Francis Bond', 'Time': '2012'}]
Background
- Research interests include understanding how humans learn and represent complex and evolving information in the context of large-scale and noisy environments; and using these insights to develop fairer and more robust automatic systems. Combines methods from natural language processing, machine learning, and computational cognitive modeling. Representative projects include scalable models of category and feature learning in children from noisy language data; and modeling the historical change of word meaning over centuries. Current research focuses on improving the automatic understanding of narratives, both in fiction (e.g., inducing structured representations of novels; or movie summarization) and in reality, by analyzing framing and narrative strategies in (biased) news stories.
