Name: Hongmin Cai
Introduction:
Professor
Room B5-514
School of Computer Science & Engineering
South China University of Technology
Guangzhou Higher Education Mega Centre
510006, Guangzhou
P. R. China
Tel: 020-39380285
E-mail: hmcai@scut.edu.cn
Academic Qualifications
2016.09－now Professor School of Computer Science and Engineering South China University of Technology
2013.06－2013.09 Visiting Professor Institute of Chemical Research Kyoto University
2012.04－2016.09 Associate Professor School of Computer Science and Engineering South China University of Technology
2008.09－2012.03 Assistant Professor School of Information Science and Technology Sun Yat-sen University
2006.07－2006.12 Visiting Scholar Section for Biomedical Image Analysis University of Pennsylvania
2005.04－2005.10 Visiting Scholar Center for Bioinformatics Harvard University
2003.09－2007.10 Ph.D. Applied Mathematics University of Hong Kong
2001.09－2003.07 M.S. Applied Mathematics Harbin Institute of Technology
1997.09－2001.07 B.S. Information and Computational Science Harbin Institute of Technology
Areas of Professional Interest
Biomedical Image segmentation and posterior analysis, feature selection for bio-data, bioinformatics, big data integration
Scientific Honors and Professional Services
PC member, ICDKE 2012
Co-chair, DANTH 2013(PAKDD)
Associate Editor, Journal of Bioinformatics Research Studies
Committee member of System Biology Committee in China Operation Federation
Committee member of Bioinformatics and Artificial Life Committee in China Artificial Intelligence Federation
Committee member of Bioinformatics in CCF
Publications
Journal Papers
(1)Cai H, Xu X, Lu J, Lichtman J, Yung SP, and Wong STC, Repulsive snake model segments and tracks neurons in 3D microscopy image stacks, NeuroImage, vol. 32, pp.1608-1620, 2006. (IF5.288)
(2)Verma R, Zacharaki E, Ou Y, Cai H, and Davatzikos C, Multiparametric tissue characterization of brain neoplasms and their recurrence using pattern classification of MR images, Academic Radiology, vol. 15, issue 8,pp.966-77,2008 (Impact factor 2.094). (IF 1.78)
(3)Cai H, Xu X, Lu J, Lichtman J, Yung SP, and Wong STC, Using nonlinear diffusion and mean shift to detect and connect cross-sections of axons in 3D optical microscopy images, Medical Image Analysis, vol. 12, issue 6, pp. 666-675, 2008. (IF3.505)
(4)Cai H, Cui C, Tian H, Li L, A Novel Approach to Segment and Classify Regional Lymph Nodes on Computed Tomography Images, Computational and Mathematical Methods in Medicine, vol. 2012. （IF0.682）
(5)Wan, Xiang-Bo, Zhao, Yan, Fan, Xin-Juan, Cai, Hong-Min#, Zhang, Yan, Chen, Ming-Yuan, Molecular Prognostic Prediction for Locally Advanced Nasopharyngeal Carcinoma by Support Vector Machine Integrated Approach, Plos One, 7(3), 2012/3/9. (IF4.411)
(6)Fan, X-J, Wan, X-B, Huang, Y., Cai, H-M, Fu, X-H, Yang, Z-L, Chen, D-K, Song, S-X, Wu, P-H, Liu, Q., Wang, L., *Wang, J-P Epithelial-mesenchymal transition biomarkers and support vector machine guided model in preoperatively predicting regional lymph node metastasis for rectal cancer, British Journal of Cancer, 106(11), pp 1735-1741, 2012/5/22. (IF5.042)
(7)Cui C, Cai H*, Tian H, Lai J, Li L, Quantitative Analysis and Prediction of Lymph Node Status in Rectal Cancer Based on Computed Tomography Imaging, European Radiology, vol. 21(11), pp.2318-2325, 2011. (IF3.594)
(8)崔春艳, 李立, 蔡宏民, 田海英, 刘立志, 张敏，直肠癌肠旁淋巴结CT图像相关影像学参数定量化分析，中国CT和MRI杂志, 04期, pp 35-38, 2011.
(9)Weifeng Su, Hejun Wu, Yafei Li, Jing Zhao, Fred Lochovsky, Hongmin Cai, and Tianqiang Huang. Understanding Query Interfaces by Statistical Parsing.ACM Transaction on Web (TWeb), 2013. (IF0.87)
(10)Hongmin Cai, Yanxia Peng, CaiwenOu,Minsheng Chen and Li Li, Diagnosis of breast masses from dynamic contrast-enhanced and diffusion-weighted MR: a machine learning approach, PLOS ONE, 2014, DOI: 10.1371/journal.pone.0087387 (IF3.73)
(11)Hongmin Cai, Zhong Yan, Weiming Xia, and Xiaoyin Xu, A new iterative tri-class thresholding technique in image segmentation, IEEE Transaction on Image Processing, 2014, 23(3), 1038-1046.(IF3.199)
(12)Hongmin Cai, Peiying Ruan , Michael Ng,and Tatsuya Akutsu, Feature weight estimation for gene selection: a local hyper linear learning approach, BMC Bioinformatics, 2014, 15:70DOI: 10.1186/1471-2105-15-70. (IF3.02)
(13)Xiaoping Cheng, Hongmin Cai*, Ping He,Yue Zhang and Runtiao Tian, Combination of effective machine learning techniques and chemometric analysis for evaluation of Bupleuri Radix through high-performance thin-layer chromatography, Anal. Methods, 2013,5, 6325-6330. (IF1.292)
(14)Hongmin Cai, Lizhi Liu, Yanxia Peng, Yaopan Wu, and Li Li, Diagnostic assessment by dynamic contrast-enhanced and diffusion-weighted MR in differentiation of breast lesions under different imaging protocols, BMC Cancer, 2014, 14:366. (IF3.33)
(15)Haiying Tian, Hongmin Cai, Jianhuang Lai, A Novel Impulse Noise Removal System Based on Robust Diffusion Tensor, Neurocomputing, 133(10), 2014, 222–230.
(16)Xiaoping Chen, Hongmin Cai*, et al., Optimal combination of feature selection and classification via local hyperplane based learning strategy, BMC Bioinformatics, 16:219, 2015. (IF3.02)
(17)Rou Jiang, Mingyuan Chen, et al., Hongmin Cai£, `` Development of a Ten-Signature Classifier using a Support Vector Machine Integrated Approach to Subdivide the M1 stage into M1a and M1b stages of Nasopharyngeal Carcinoma with Synchronous Metastases to Better Predict Patients' Survival”, Oncotarget 19;7(3):3645-57. (IF6.5)
(18)Jinhua Wang, Xi Yang, Hongmin Cai£, Wanchang Tan, Cangzheng Jin, Li Li, Discrimination of Breast Cancer with Microcalcifications on Mammography by Deep Learning, Science Reports, 27327 (2016)
(19)Changsheng Zhang, Hongmin Cai*, et al., nbCNV: a multi-constrained optimization model for discovering copy number variants in single-cell sequencing data, BMC Bioinformatics, 17:384, 2016. (IF3.02)
(20)Bo Xu, Zhang Changsheng, Xi Yang, and Cai Hongmin*，Copy Number Variants Calling for Single Cell Sequencing Data by Multi-constrained Optimization, Comput Biol Chem, 2016 Aug, 63:15-20.
(21)Xi Yang, Guoqiang Han, Hongmin Cai*, Yan Song, Recovering hidden diagonal structures via non-negative matrix factorization with multiple constraints，IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2017. (IF1.609)
Conference Papers
(1)Cai H, Xu X, Lu J, Lichtman J, Yung SP, and Wong STC, Segment and Track Neurons in 3D by Repulsive Snake Method, Proceedings of the 2005 International Symposium on Intelligent Signal Processing and Communication Systems, pp. 529-531, Hong Kong, P.R. China, 2005.12.13-12.16
(2)Cai H, Xu X, Lu J, Lichtman J, Yung SP, and Wong STC, Use mean shift to track neuronal axons in 3D, Life Science Systems and Applications Workshop, IEEE/NLM, pp. 1-2, Bethesda, MD, USA, 2006.7.13-7.14
(3)Cai H, Verma R, Ou Y, Lee S, Melhem E.R, and Davatzikos C, Probabilistic Segmentation of Brain Tumor on Multi-modaility MRI, Proc International Symposium of Biomedical Imaging ISBI 2007, pp:600 – 603, Washington D.C., USA, 2007.4.12-4.16
(4)Chen J, Xu X, Cai H, Miller L, and Wong STC, A new snake algorithm to track neuronal structure in microscopy image, Proceedings of the 2005 International Symposium on Intelligent Signal Processing and Communication Systems, pp. 537-541, Hong Kong, P.R. China,
(5)Cai H, Xu X, Lu J, Lichtman J, Yung SP, and Wong STC, Shape-constrained repulsive snake method to segment and track neurons in 3D microscopy images, Proc International Symposium of Biomedical Imaging ISBI 2006, pp. 538-541, Arlington, VA, USA, 2006.4.6-4.9
(6)Zhang Y, Xu X, Cai H, Yung SP, and Wong STC, New Nonlinear Diffusion Method to Improve Image Quality, IEEE International Conference on Image Processing, ICIP 2007, San Antonio, Texas, USA, 2007.9.16-9.19
(7)H. Y Tian, Cai H*, Cui C, Lai J, Li L “Quality enhancement with adaptive edge preservation for lymph nodal images”, AIP Conference Proceedings, 2011 International Symposium on Computational Models for Life Sciences, Vol.1371(1), pp. 341-342, Toyama, Japan, 2011.10.11-10.13
(8)H. Y Tian, Cai H*, Lai J, Improved Partial Differential Equation-based Method to Remove Noise in Image enhancement, WIAMIS 2011: 12th International Workshop on Image Analysis for Multimedia Interactive Services, Delft, The Netherlands, 2011.4.13-4.15
(9)田海英，蔡宏民*，赖剑煌，边缘检测新算子及其在去噪方面的应用，《第十五届全国图象图形学学术会议论文集》，2010，中国广州，2010.12.10-12.11
(10)H.Y Tian, Cai H*, Lai J, X.Y Xu, Image noise removal based on a new edge indicator, ICIP 2011, Brussels, Belgium, 2011.9.11-9.14
(11)Cai H，Improvements over adaptive local hyperplane to achieve better classification, ICDM 2011, Vancouver, Canada, 2011.12.11-12.14
(12)Cai H，Michale Ng, Feature selection by RELIEF through local hyperplane approximation, PAKDD 2012, , Kuala Lumpur, Malaysia, 2012.5.29-6.1
(13)Cai H，Michale Ng, Optimal combination of feature weight learning and classification based on local approximation, ICDKE 2012, Wuyishan, P.R. China, 2012.11.21-11.23
(14)Chen P, Huang W, Shao W, Hongmin Cai*, Discrimination of recurrent CNVs from individual ones from multisample aCGH by jointly constrained minimization, ACM BCB 2015, Atlanta, the United States (U.S.), 2015.9.9-9.12
(15)Li Tengpeng, Zhang Changsheng, Bo Xu, Li Fuqiang, and Cai Hongmin*, MALBACsim: a Multiple Annealing and Looping Based Amplification Cycles Simulator, BIBM 2015,Washington D.C., the United States (U.S.), 2015.11.9-11.12
(16)Bo Xu, Zhang Changsheng, Xi Yang, and Cai Hongmin*, Copy Number Variants Calling for Single Cell Sequencing Data by Multi-constrained Optimization, APBC 2016, San Francisco, the United States (U.S.), 2016.1.11-1.13
(17)Weihen Huang, Hongmin Cai*, et. Al., MDAGenera: An Efficient and Accurate Simulator for Multiple Displacement Amplification, ICIC 2016, Lanzhou, P.R. China, 2016.8.2-8.5
(18)Zhang Changsheng, Cai Hongmin*“, and et. Al., Multi-norm Constrained Optimization Methods for Calling Copy Number Variants Calling in Single Cell Sequencing Data, BIBM 2016, Shenzhen, P.R. China, 2016.12.15-12.18
Projects
(1)NSF for youth project, PI,2009.1-2010.12
(2)NSF of Guangdong Province, PI,2016.1 - 2017.12
(3)BGI-SCUT Innovation Fund Project (SW20130803), PI, 2013.08-2015.08
(4)National Nature Science Foundation of China (61372141), PI, 2014.1 - 2017.12
Scientific Awards
(1)The Program of “Thousand, hundred and ten talents in Guangdong” University award, 2014
(2)Outstanding Youth Teacher Award in Guangdong, 2014
(3)Professor in Advance, 2014
