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Dr. LIU, Yang 劉泱
Ph.D., M.Eng., B.Eng.
Assistant Professor, Department of Computer Science

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Dr. Liu is currently an Assistant Professor in the Department of Computer Science at Hong Kong Baptist University. He received his B.Eng. and M.Eng. degrees in Automation from National University of Defense Technology in 2004 and 2007, respectively. He received the Ph.D. degree in Computing from The Hong Kong Polytechnic University in 2011. During Feb.-Aug. 2010, he was a Visiting Scholar in the Robotics Institute at Carnegie Mellon University. Between 2011 and 2012, he was a Postdoctoral Research Associate in the Department of Statistics at Yale University. Dr. Liu's research interests include artificial intelligence, machine learning, applied mathematics, as well as their applications in high-dimensional/heterogeneous data analytics, computational epidemiology, and infectious disease modeling. He has published more than 70 peer-reviewed papers in reputable venues, including the top journals such as The Lancet's EClinicalMedicine, T-NNLS, T-Cyber, T-IP, T-AC, T-AMD, T-IST, PR, and NeuroImage, as well as top conferences such as AAAI, IJCAI, SIGIR, and ACMMM.

Research Interests

  • Artificial Intelligence, Machine Learning, Pattern Recognition
  • Dimensionality Reduction, Subspace Learning
  • Multi-way/Multi-view/Multi-label/Multi-task Learning
  • Computational Epidemiology, Infectious Disease Modeling

Selected Publications

  • Yang Liu, Zhonglei Gu, Shang Xia, Benyun Shi, Xiao-Nong Zhou, Yong Shi, and Jiming Liu, What are the underlying transmission patterns of COVID-19 outbreak? – An age-specific social contact characterization, EClinicalMedicine, The Lancet Journals, In Press: April, 2020.
  • Tiantian He*, Yang Liu*, Tobey H. Ko, Keith C.C. Chan, and Yew-Soon Ong, Con-textual Correlation Preserving Multi-View Featured Graph Clustering, IEEE Transactions on Cybernetics (T-Cyber), In Press: 2020. (Joint First Author)
  • Yang Liu, Zhonglei Gu, Tobey H. Ko, and Jiming Liu, Identifying Key Opinion Leaders in Social Media via Modality-Consistent Harmonized Discriminant Embedding, IEEE Transactions on Cybernetics (T-Cyber), 50(2), pp.717–728, 2020.
  • Yang Liu, Tobey H. Ko, and Zhonglei Gu, Who is the Mr. Right for Your Brand? – Discovering Brand Key Assets via Multi-modal Asset-aware Projection, in Proceedings of 41st International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-18), pp.1113–1116, 2018.
  • Kejing Yin, William K. Cheung, Yang Liu, Benjamin C. M. Fung, and Jonathan Poon, Joint Learning of Phenotypes and Diagnosis-Medication Correspondence via Hidden Interaction Tensor Factorization, in Proceedings of 27th International Joint Conference on Artificial Intelligence (IJCAI-18), pp.3627–3633, 2018.
  • Jiabei Zeng, Yang Liu, Biao Leng, Zhang Xiong, and Yiu-ming Cheung, Dimensionality Reduction in Multiple Ordinal Regression, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 29(9), pp.4088–4101, 2018.
  • Yan Liu, Yang Liu, Shenghua Zhong, and Songtao Wu, Implicit Visual Learning: Image Recognition via Dissipative Learning Model, ACM Transactions on Intelligent Systems and Technology (TIST), 8(2), 31:1-24. 2017.
  • Yang Liu, Yan Liu, Xiang Zhang, Gong Chen, and Kejun Zhang. Learning Music Emotion Primitives via Supervised Dynamic Clustering, in Proceedings of 24th ACM International Conference on Multimedia (ACM MM), 2016.
  • Yang Liu, Yan Liu, Yu Zhao, and Kien A. Hua. What Strikes the Strings of Your Heart? – Feature Mining for Music Emotion Analysis, IEEE Transactions on Affective Computing (TAC), 6(3), pp. 247-260, 2015.
  • Yang Liu, Yan Liu, Keith C.C. Chan, and Kien A. Hua. Hybrid manifold embedding, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 25(12), pp. 2295-2302, 2014.
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Department of Computer Science, Hong Kong Baptist University
Hong Kong Baptist University