Tel: +44 24 765 73793
Email: Yulan dot He at warwick dot ac dot uk
Yulan He is a Professor of Computer Science at the University Warwick. Prior joining Warwick, she was a Reader in Computer Science and the Director of the Systems Analytics Research Institute at Aston University. Before that, she held the academic positions at the Knowledge Media Institute of the Open University, the University of Exeter and the University of Reading. She has published over 150 papers in the areas of text and data mining, sentiment analysis and opinion mining, social media analysis, recommender systems, learning analytics and spoken dialogue systems. In the past, she has served as an Area Chair in top natural language processing conferences including ACL, EMNLP and NAACL and a Senior Programme Committee member in AAAI and IJCAI.
Yulan obtained her PhD degree in spoken language understanding from the University of Cambridge, and her MEng and BASc (First Class Honours) degrees in Computer Engineering from Nanyang Technological University, Singapore.
Yulan's research centres on the exploration of statistical models in representing uncertainty and the benefit they bring over earlier work in a wide range of application areas, particularly the integration of machine learning and natural language processing for text understanding.
Some of her interested research topics include:
- Sentiment analysis and opinion mining. Exploration of machine learning and deep learning techniques for the understanding of sentiments and opinions expressed in text.
- Natural language processing. Topic, event and storyline extraction from text; conversational agents.
- Social media analysis. Combining content modelling and social network analysis for understanding online user behaviours.
- Clinical text mining. Investigation of statistical models for automated extraction of information from clinical documents.
Research Projects (since 2013)
- DeepPatient: Deep Understanding of Patient Experience of Healthcare in Social Media (2018 - 2020). MSCA Fellowship funded by the EU-H2020.
- Data Analytics for Future Cities Research (2018), Researcher Links Workshop Grants funded by the British Council.
- Big Data Content Analytics (2017 - 2019). cR&D project funded by the Technology Strategy Board (TSB).
- Opinion Cluster Detection from Social Media (Jan 2016 - Dec 2017). Funded by the Overseas Collaboration Fund of Natural Science Foundation of China in collaboration with Southeast University.
- Data fusing and integration from multiple resources (2015 - 2018). A Knowledge Transfer Partnership (KTP) project in collaboration with Integrated Geochemical Interpretation Ltd funded by the Innovate UK.
- Big Data: Digitisation, Semantic Analysis, Topic Modelling, Visualisation and Exploration (2014 - 2016). cR&D project funded by the Technology Strategy Board (TSB) under the big data exploitation call.
- ReDites: real time, detection, tracking, monitoring and interpretation of events in social media (2013 - 2014). Funded by the EPSRC.
(Click here for full publication list)
- L. Zhu, Y. He and D. Zhou. Hierarchical Viewpoint Discovery from Tweets Using Bayesian Modelling. Expert Systems with Applications, 116:430-438, 2019.
- D. Tang, Z. Zhang, Y. He, C. Lin and D. Zhou. Hidden Topic–Emotion Transition Model for Multi-Level Social Emotion Detection, Knowledge-Based Systems, to appear.
- Y. Yang, D. Zhou and Y. He. An Interpretable Neural Network with Topical Information for Relevant Emotion Ranking. The 15th International Conference on Empirical Methods on Natural Language Processing (EMNLP), Brussel, Belgium, Oct. 2018.
- J. Du, W. Li, Y. He, L. Bing, R. Xu and X. Wang. Variational Autoregressive Decoder for Neural Response Generation, The 15th International Conference on Empirical Methods on Natural Language Processing (EMNLP), Brussel, Belgium, Oct. 2018.
- D. Zhou, Z. Zhang, M. Zhang and Y. He. Weakly Supervised Part-of-Speech (POS) Tagging without Disambiguation, ACM Transactions on Asian and Low-Resource Language Information Processing, 17(4):Article 35, 2018.
- D. Zhou, L Miao and Y. He. Position-Aware Deep Multi-Task Learning for Drug-Drug Interaction Extraction. Artificial Intelligence in Medicine, 87:1-8, 2018.
- T. Bai, W.X. Zhao, Y. He, J-Y. Nie and J.-R. Wen. Characterizing and Predicting Early Reviewers for Effective Product Marketing on E-Commerce Websites. IEEE Transactions on Knowledge and Data Engineering, 30(12):2271-2284, 2018.
- D. Zhou, Y. Yang and Y. He. Relevant Emotion Ranking from Text Constrained with Emotion Relationships, The 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL), New Orleans, Louisiana, USA, Jun. 2018.
- D. Zhou, L. Guo and Y. He. Neural Storyline Extraction Model for Storyline Generation from News Articles, The 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL), New Orleans, Louisiana, USA, Jun. 2018.
- U. Orizu and Y. He. Content-Based Conflict-of-Interest Detection on Wikipedia, The 11th International Conference on Language Resources and Evaluation (LREC), Miyazaki, Japan, May 2018.
- V. Batra, Y. He and G. Vogiatzis. A Deep Learning Approach to Automatic Caption Generation for News Images, The 11th International Conference on Language Resources and Evaluation (LREC), Miyazaki, Japan, May 2018.
- G. Pergola, Y. He and D. Lowe. Topical Phrase Extraction from Clinical Reports by Incorporating both Local and Global Context, The 2nd AAAI Workshop on Health Intelligence, New Orleans, Louisiana, USA, Feb. 2018.
- W.X. Zhao, W. Zhang, Y. He, X. Xie and J.-R. Wen. Automatically Learning Topics and Difficulty Levels of Problems in Online Judge Systems. ACM Transactions on Information Systems, Vol. 36, No. 3, Article 27, 2018.
I am hiring a Research Fellow in text analytics, please click here for more information.