Rate My Professor Trevor Cohn
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Fosters a love for lifelong learning.
Always kind, respectful, and approachable.
Makes learning feel effortless and fun.
Helps students see their full potential.
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About Trevor
Professor Trevor Cohn is a Professor in the School of Computing and Information Systems within the Faculty of Engineering and Information Technology at the University of Melbourne. He holds a PhD from the University of Melbourne, a Postgraduate Certificate from the University of Sheffield, and a Bachelor's degree. His career at the University of Melbourne progressed from Lecturer to Senior Lecturer and ARC Future Fellow (2014-2020), Associate Professor, and now full Professor. In April 2023, he took up a dual appointment as Research Scientist at Google Research Australia in Sydney, where he spends the majority of his time. Since February 2022, he has served as Director of the ITTC on medtech, succeeding Tim Baldwin. Cohn served as Local Chair for ACL 2018 in Melbourne alongside Tim Baldwin and Karin Verspoor, and as Program Co-Chair for EMNLP 2020 with Yang Liu and Yulan He.
Cohn's research centers on probabilistic machine learning models for natural language processing, with applications in automatic translation, structured prediction, handling uncertain data, multilingual machine translation, and fairness in NLP. Key publications include 'Tangled Up in BLEU: Reevaluating the Evaluation of Automatic Machine Translation Evaluation Metrics' (ACL 2020, honorable mention best paper), 'Backdoor Attacks on Multilingual Machine Translation' (NAACL 2024), 'SEEP: Training Dynamics Grounds Latent Representation Search for Mitigating Backdoor Poisoning Attacks' (TACL 2024), 'Revisiting subword tokenization: A case study on affixal negation in large language models' (NAACL 2024), and 'Planning in the Dark: LLM-Symbolic Planning Pipeline without Experts' (AAAI 2025). Under his supervision, students received awards such as the AACL best paper runner-up (2022), CORE John Makepeace Bennett Australasian Distinguished Doctoral Thesis Award (2022), and ACL best paper honorable mention (2020). His work has garnered over 16,600 citations with an h-index of 65 (Google Scholar), reflecting significant impact in computational linguistics and machine learning.
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