|Academic Profile |
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Assoc Prof Lin Feng
School of Computer Engineering
College of Engineering
Phone: (+65)6790 6184
- PhD Nanyang Technological University 1997
- MEng Zhejiang University 1986
- BEng Zheijiang University 1983
|Dr Lin Feng is currently an Associate Professor, the Director of Bioinfomatics Research Centre and the Programme Director of MSc (Digital Media Technology) at School of Computer Engineering, Nanyang Technological University. He has worked for more than 20 funded research projects since joining NTU and has published about 200 technical papers including more than 80 in journals of high impact factors, edited books and chapters; he has been serving Editorial Board, Guest Editor / Reviewer for tens of journals and books; and he has won 7 prestigious research awards, including the “National Science and Technology Advance Award (Second Class)” by Chinese State Council. He is a Senior Member of IEEE.|
|Dr Lin's research interest includes biomedical informatics, biomedical imaging and visualization, computer graphics, high-performance computing. Currently active funded projects include: AcRF - Nonrigid graphics shaders for GPU, AcRF - Physiologically-Based Modelling and Visualization of a Beating Heart, A-Star/BMRC - Creating an In Vivo Navigational Cellular Fluorescence Imaging System with Dynamically Optimized Endomicroscopy, AcRF - Real-time Diagnostic Endomicroscopy, A-Star/SERC - Collaborative Creation and Application of Interactive Digital Media over the Internet, AcRF - Cellular Fluorescence Imaging with Endomicroscopy, AcRF - Dynamically Adaptable Neurocomputer and Its Application to Recognition of Steroid Hormone Response Elements, SingHealth Foundation Development of a Real-time Fluorescence Endoscopy Diagnostic System for the Early Detection of Oral and Bladder Cancers, NTU/BPE Cluster SEED Funding - Gene Expression Profiling with Oligonucleotide Microarray Technology; and some completed funded projects: SCE ER Lab Research Programme Grant DNA Chip Design Programme, BMRC&NMRC Joint Research Fund - Elucidation of Expression Profiles of Genes in Alpha-fetoprotein Positive and Alpha-fetoprotein Negative Hepatocellular Carcinoma by cDNA Microarray Analysis, AcRF - Design and Simulation of Artificial Bone Implantation, NMRC Research Fund -Nasopharyngeal Carcinoma: 3D Imaging for Staging and Treatment Planning, AcRF - Design and Development of Bio-medical Devices Using Rapid Prototyping (RP) Techniques, AcRF - Real-time Dynamic Simulation, MOH & Singapore Totalisator Research Fund - Transforming Medical Ultrasound Scanning into 3-Dimensional Real-time Organ Imaging to Aid Clinical Diagnosis.|
- Academic Research Fund Tier 1 (2013-)
- Academic Research Fund Tier 1 (2015-)
- Academic Research Fund Tier 2 (2012-2015)
- An Immersive Virtual Endomicroscopic Environment - Towards Innovation in Photodynamic Therepy for Mucosal Cnacer
- In Silico Modelling of Ageing and Stem Cell Based Rejunenation on Waddington's Epigenetic Landscape
- Multi-Model Medical Imaging And Informatics For PACS & RIS
- Nonrigid Graphics Kernels for GPU
- Physiologically-Based Modeling for Anatomical Structures
- Physiologically-Based Modelling and Visualization of a Beating Heart
- Qian Kemao, Haixia Wang, Wenjing Gao, Lin Feng, Seah Hock Soon. (2010). Phase extraction from arbitrary phase-shifted fringe patterns with noise suppression. Optics and Lasers in Engineering, 48(6), 684-689.
- Han Xu, Lusy Handoko, Xueliang Wei, Chaopeng Ye, Jianpeng Sheng, Chia-Lin Wei, Feng Lin*, Wing-Kin Sung. (2010). A Signal-Noise Model for Significance Analysis of ChIP-seq with Negative Control. Bioinformatics, 26(9), 1199-1204.
- Lin Feng, Malini Olivo, Kung Sun-Yuan. (2009). Biomedical Imaging. Springer Science+Business Media, LLC, ISBN 978-1-4419-1165-0.
- Menaka Rajapakse, Lin Feng. (2009). Prediction and Characterization of MHC-Peptide Binding Sites. IEEE Engineering in Medicine and Biology Magazine, 28(4), 73-77.
- Menaka Rajapakse, Bertil Schmidt, Lin Feng, Vladimir Brusic. (2007). Predicting peptides binding to MHC class II molecules using multi-objective evolutionary algorithms. BMC Bioinformatics, 8(22), 459.