HKBU  |  SCI  |  BUniPort  |  Library  |  Alumni  |  Job Vacancies  |  Intranet  |  Sitemap        
Undergraduate Admissions
Taught Postgraduate Admissions
Research Postgraduate Admissions
News & Achievements
Research Highlights
Contact & Direction
Dr. LAN, Liang 蘭亮
B.Eng., M.Sc., Ph.D.
Assistant Professor, Department of Computer Science

Personal Website:

Dr. Liang Lan is currently an assistant professor in the department of computer science at Hong Kong Baptist University. He was an advisory researcher and a senior researcher with Lenovo Machine Intelligence Research Center, Hong Kong from 2016 to 2018. Before that, he was a research scientist at Institute for Infocomm Research, Singapore from 2014 to 2016, and a researcher with Huawei Noah’s Ark Lab, Hong Kong from 2013 to 2014. He received his Ph.D. degree in Computer and Information Sciences from Temple University, Philadelphia, USA in 2012 and his B.Eng. degree in Bioinformatics from Huazhong University of Science and Technology, Wuhan, China in 2007. His research interests include large scale machine learning algorithms, in particular in support vector machines, kernel learning, deep neural networks and their applications in health informatics and bioinformatics. He has published several papers in the top venues, such as AIJ, JMLR, TNNLS, ICML and AISTATS. He is the recipient of the Institution of Engineers Singapore (IES) Prestigious Engineering Achievement Award 2015 and 2016 and the ASEAN Outstanding Engineering Achievements Award 2016.

Research Interests

  • Machine Learning
  • Deep Neural Networks
  • Health Informatics
  • Bioinformatics

Selected Publications

  • Lan, L., Zhang, K., Ge, H., Cheng, W., Zhang, J., Liu, J., Rauber, A., Li, X., Wang, J., Zha, H., Low-rank Decomposition Meets Kernel Learning: A Generalized Nystrom Method, Artificial Intelligence Vol. 250, pp. 1–15, 2017.
  • Zhang, K., Lan, L., Kwok, T.J., Vucetic, S., Parvim, B., Scaling Up Graph-Based Semisupervised Learning via Prototype Vector Machines, IEEE Transactions on Neural Networks and Learning Systems, Vol. 26 (3), pp. 444-457, 2015.
  • Lan, L., Malbasa, V., Vucetic, S., Spatial Scan for Disease Mapping on a Mobile Population, in Proceeding of the AAAI Conference on Artificial Intelligence (AAAI), 2014.
  • Djuric, N., Lan, L., Vucetic, S., Wang, Z., BudgetedSVM: A Toolbox for Large-Scale Non-linear SVM, Journal of Machine Learning Research, 14, 3813-3817, 2013.
  • Lan, L., Vucetic, S., Multi-task Feature Selection in Microarray Data by Binary Integer Programming, BMC Bioinformatics, Vol. 7 (Suppl. 7): S5, 2013.
  • Lan, L., Djuric, N., Guo, Y., Vucetic, S., MS-kNN: Protein Function Prediction by Integrating Multiple Data Sources, BMC bioinformatics, Vol. 14 (Suppl. 3): S8, 2013.
  • Zhang, K., Lan, L., Liu, J., Rauber, A., Moerchen, F., Inductive Kernel Low-rank Decomposition with Priors, in Proceedings of the Twenty-Ninth International Conference on Machine Learning (ICML), 2012.
  • Zhang, K., Lan, L., Wang, Z., Moerchen, F. Scaling up Kernel SVM on Limited Resources: a Low-rank Linearization Approach, Int. Conf. on Artificial Intelligence and Statistics (AISTATS), JMLR W&CP 22: 1425-1434, 2012.
  • Wang, Z., Lan, L., Vucetic, S. Mixture Model for Multiple Instance Regression and Applications in Remote Sensing, IEEE Transactions on Geoscience and Remote Sensing (TGRS), vol. 50, no. 6, pp.2226-2237 2012.
Copyright © 2021. All rights reserved.Privacy Policy
Department of Computer Science, Hong Kong Baptist University
Hong Kong Baptist University