Michael Schlichtkrull

Dr. Michael Schlichtkrull is a Lecturer at Queen Mary University of London (QMUL) and a Research Associate at Fitzwilliam College, Cambridge. His research focuses on automated reasoning over retrieved evidence, particularly for fact-checking and complex epistemological problems. He also explores structured data modeling, including knowledge graphs, tables, and parse trees. Prior to QMUL, he was a postdoctoral researcher at the University of Cambridge (working with Andreas Vlachos on automated fact verification) and earned his PhD (2021) from the University of Amsterdam (under Ivan Titov), where he developed NLP models incorporating structured data.

Teaching: He instructs the Risk and Decision Making with Artificial Intelligence course (IOT7005P). Research Interests include automated fact-checking, graph neural networks, and interpretability in NLP. He has contributed to datasets like AVeriTeC and organized the FEVER workshop series. His work addresses challenges in multimodal fact-checking, ethical AI, and NLP model limitations.

Grants: He leads the EPSRC-funded project Addressing socio-technical limitations of LLMs for medical and social computing (£1.8M), focusing on improving large language models' trustworthiness and societal impact. Collaborations span institutions like the University of Cambridge and industry partners.

Labs/Teams: Affiliated with Queen Mary’s Centre for Human-Centred Computing, emphasizing AI applications that prioritize human needs and ethical considerations.