|Asst Prof Lian Heng |
Division of Mathematical Sciences
School of Physical & Mathematical Sciences
College of Science
- PhD (Applied Maths) Brown University 2007
- MS (Computer Science) Brown University 2005
- MA (Economics) Brown University 2005
- BS (Computer Science) University of Sci. & Tech. of China 2000
- BS (Mathematics) University of Sci. & Tech. of China 2000
|Asst/Prof Lian Heng is currently in the School of Science since 2007. He received his Bachelor degree in Mathematics and Computer Science from University of Science and Technology of China, Master in Computer Science and Economics and Ph.D. in Applied Mathematics from Brown University, USA. His research interests include Bayesian statistics, bioinformatics and pattern theory.|
|Asst Prof Lian Heng?s areas of expertise are Pattern recognition and machine learning, Bayesian analysis with applications to biological and financial data, functional modeling.|
|Research Grant |
- Academic Research Fund Tier 1 (2010-)
- Academic Research Fund Tier 1 (2012-)
|Current Projects |
- Extending the Scope of Functional Data Analysis with Applications
- Hierarchical Bayesian change point models: theory and applications
- Semiparametric Models for Longitudinal Data: Random Effects, Fixed Effects, and Variable Selection
- Y. Hu, R. Gramacy and H. Lian. (2013). Bayesian quantile regression for single-index models. Statistics and Computing, .
- H. Lian. (2013). Shrinkage estimation and selection for multiple functional regression. Statistica Sinica, .
- H. Lian, X. Chen and Jian-Yi Yang. (2012). Identification of partially linear structure in additive models with an applications to gene expression prediction from sequences. Biometrics, .
- Chopra A, Lian H. (2010). Total variation, adaptive total variation and nonconvex smoothly clipped absolute deviation penalty for denoising blocky images. Pattern Recognition, 43(8), 2609-2619.
- Lian H. (2009). Bayesian Nonlinear Principal Component Analysis Using Random Fields. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31, 749-754.