Christopher Davis

Christopher Davis is a postdoctoral researcher in the Natural Language and Information Processing group at the University of Cambridge, affiliated with the ALTA Institute. His work focuses on computational models for grammatical error detection and correction in second language learner text, leveraging large language models and multimodal semantics.

Research Interests: Davis specializes in

• Natural Language Processing
• Grammatical Error Correction
• Multimodal Semantics
• Curriculum Learning
• Language Assessment Technology
• Second Language Acquisition

Publications: His research explores the intersection of grammatical error detection, multimodal semantics, and curriculum learning, with recent works applying large language models to educational settings and probing syntactic knowledge in NLP systems.

Scientific Awards:

• Most Interesting Paper Award, BabyLM Challenge @ CoNLL 2023

Teaching Roles: Davis has supervised and demonstrated modules like Formal Models of Language and Machine Learning and Real-world Data at the University of Cambridge. He also served as an external tutor for Neural Networks and Natural Language Processing at the Cambridge Spark Applied Data Science Bootcamp.

Contact:

• Email: ccd38@cl.cam.ac.uk