Dr Juntao Yu
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Email
j.yu@essex.ac.uk -
Location
Colchester Campus
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Academic support hours
My support hour is 2 - 4 pm on Monday via Zoom. For the meeting link please check the course Moodle page.
Profile
Biography
I am a Lecturer at the University of Essex. Before that, I was a post-doctoral researcher at the Queen Mary University of London, working with Professor Massimo Poesio on his five-year DALI project (Disagreements and Language Interpretation, ERC-2015-AdG). I did my PhD at the University of Birmingham, working on out-of-domain dependency parsing. I was supervised by Dr Bernd Bohnet, Professor John Barnden and Dr Mark Lee. My research interests include Deep Learning for NLP, Information Extraction, Coreference Resolution, Conversational AI, Dependency Parsing, Domain Adaptation, Semi-supervised Learning, and Multi-task Learning.
Qualifications
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PhD Computer Science University of Birmingham, (2017)
Appointments
University of Essex
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Lecturer in Natural Language Processing, School of Computer Science and Electronic Engineering, University of Essex (2021 - present)
Other academic
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Postdoctoral Researcher, School of Electronic Engineering and Computer Science, Queen Mary University of London (2017 - 2021)
Research and professional activities
Research interests
Deep Learning for NLP
Information Extraction
Coreference Resolution
Conversational AI
Low Resource Learning
Teaching and supervision
Current teaching responsibilities
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Information Retrieval (CE306)
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Information Retrieval (CE706)
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ICT Systems Integration and Management (CE719)
Publications
Conferences (17)
Yu, J., Moosavi, NS., Paun, S. and Poesio, M., (2021). Stay Together: A System for Single and Split-antecedent Anaphora Resolution.
Khosla, S., Yu, J., Manuvinakurike, R., Ng, V., Poesio, M., Strube, M. and Rosé, C., (2021). The CODI-CRAC 2021 Shared Task on Anaphora, Bridging, and Discourse Deixis in Dialogue
Yu, J., Bohnet, B. and Poesio, M., (2020). Neural Mention Detection.
Yu, J., Bohnet, B. and Poesio, M., (2020). Named Entity Recognition as Dependency Parsing.
Yu, J. and Poesio, M., (2020). Multitask Learning-Based Neural Bridging Reference Resolution.
Yu, J., Moosavi, NS., Paun, S. and Poesio, M., (2020). Free the Plural: Unrestricted Split-Antecedent Anaphora Resolution.
Yu, J., Uma, A. and Poesio, M., (2020). A Cluster Ranking Model for Full Anaphora Resolution.
Aloraini, A., Yu, J. and Poesio, M., (2020). Neural Coreference Resolution for Arabic
Madge, C., Yu, J., Chamberlain, J., Kruschwitz, U., Paun, S. and Poesio, M., (2019). Crowdsourcing and Aggregating Nested Markable Annotations
Poesio, M., Chamberlain, J., Paun, S., Yu, J., Uma, A. and Kruschwitz, U., (2019). A Crowdsourced Corpus of Multiple Judgments and Disagreement on Anaphoric Interpretation
Madge, C., Yu, J., Chamberlain, J., Kruschwitz, U., Paun, S. and Poesio, M., (2019). Progression in a Language Annotation Game with a Purpose
Paun, S., Chamberlain, J., Kruschwitz, U., Yu, J. and Poesio, M., (2018). A Probabilistic Annotation Model for Crowdsourcing Coreference
Poesio, M., Grishina, Y., Kolhatkar, V., Moosavi, N., Roesiger, I., Roussel, A., Simonjetz, F., Uma, A., Uryupina, O., Yu, J. and Zinsmeister, H., (2018). Anaphora Resolution with the ARRAU Corpus
Yu, J. and Bohnet, B., (2017). Dependency Language Models for Transition-based Dependency Parsing
Yu, J., Elkaref, M. and Bohnet, B., (2015). Domain Adaptation for Dependency Parsing via Self-Training
Yu, J. and Bohnet, B., (2015). Exploring Confidence-based Self-training for Multilingual Dependency Parsing in an Under-Resourced Language Scenario
Pekar, V., Yu, J., El-karef, M. and Bohnet, B., (2014). Exploring Options for Fast Domain Adaptation of Dependency Parsers
Contact
Academic support hours:
My support hour is 2 - 4 pm on Monday via Zoom. For the meeting link please check the course Moodle page.