Jia Cao, Ph.D.

Associate Professor

Institution of Information Science & Technology

Beijing Forestry University, Beijing, China

Office: +86 010 62336702

Email: caojia@bjfu.edu.cn

 

RESEARCH INTERESTS

  • Network topology (Network Science);
  • Data mining in TCM(Traditional Chinese Medicine), sociology, science and technique literatures, ecology. Data modeling by network science, data feature extraction and data analysis such as clustering analysis, association analysis and classification.

 

EDUCATION

  • 2003-2006, PhD, Institute of computing technology (ICT), Chinese Academy of Sciences. Computer science
  • 1996-2003, B.A. and M.S. Southwest Petroleum University. Computer science

 

Professional EXPERIENCE

  • 2017-2018 Visiting Scholar              San Diego State University
  • 2010 – Present Associate Professor          Beijing Forestry University
  • 2006 – 2009 lecturer                                      Beijing Forestry University

 

Funding

  • 2017-Dec.2019, Project of NSF of China (PI), Hierarchical clustering on TCM prescription with atomic attribute.
  • 2013-Oct. 2016, Project of Beijing Municipal Education Commission of China (PI), Finding specific chemical components of medicinal plants by network methods.
  • 2013-Dec.2014, Project of Fundamental Research Funds for the Central Universities (PI), Multiplex community detection on the data of chemical components of medicinal plants
  • 2006-2010, Project of National High Technology Research And Development Program Of China (Collaborator), Based on the principles of Botany research and implementation of virtual model of Populus tomentosa Carr.

 

Selected Publications

[1] Jia Cao, Hongxiao Zheng, Jinsheng Yuan. Randomness betters Nearest-Rarest in the P2P Clustering Networks.[C] WiCOM 2009.

[2] Cao Jia. Comparison about Inter-network Traffic cost of CDN-liked Approach and Cluster-based Approach in P2P Applications.[C] Proc. IITA, Shanghai, China. 2008. Vol.3: 644-648.

[3] Cao Jia. Comparison Study about Heterogeneous Size Estimation Methods.[C] Proc. CSSE, Wuhan, China. 2008. Vol.3: 303-306.

[4] J.Cao. Influence Factors of Modularity in Multiplex Networks.[C] AMSIE 2015. DEStech publications, Inc: 627-633

[5] Jia Cao. The Common Prescription Patterns based on the Hierarchical Clustering of Herb-Pairs Efficacies.[J] eCam (Evidence-Based Complementary and Alternative Medicine). 2016.

Papers in Chinese

[6] Cao Jia, Gu Hao, Wang yun. “Property Hole” Phenomenon of Chinese Medicine.[J] World Science and Technology/ Modernization of Traditional Chinese Medicine and Materia Medica. 15(1), 2013:29-33.

[7] Cao Jia, Wang Yun. Relationship between Chemical Constituents and Herbs’ Properties of Relative Plant Herbs. [J]China Journal of Chinese Materia Medica. 38(3), 2013:453-458. (MedLine)

[8] Cao Jia, Xin Juan Juan, Wang Yun. Numerical analysis on network characteristics of communities in herb-pairs network.[J] China Journal of Chinese Materia Medica. 40(11), 2015: 2199-2205. (MedLine)

[9] Cao Jia, Lu ShiWen. A Minimum Delay Spanning Tree Algorithm for the Application-Layer Multicast.[J] Journal of Software, 16(10), 2005: 1766-1773. (EI)

[10] Cao Jia, Lu ShiWen. Research on Topology Discovery in the Overlay Multicast.[J] Journal of Computer Research and Development. 43(5), 2006: 784-790. (EI)