Jinhua (Andy) MA

Post-Doctoral Fellow (CV) (Google Scholar)

Dept. of Computer Science

Hong Kong Baptist University

Email: andyjhma at comp.hkbu.edu.hk

Please visit http://isee.sysu.edu.cn/~majh/ for updates

Brief Bio

Andy J Ma received his B.Sc. and M.Sc. degrees both in Mathematics from Sun Yat-Sen University, Guangzhou, China, in 2007 and 2009, respectively. Then, he obtained his Ph.D. degree in Computer Science from Hong Kong Baptist University in 2013. His Ph.D. advisor is Prof. Pong Chi Yuen, head of the Department of Computer Science at Hong Kong Baptist University. After that, he worked as a Post-Doctoral Associate under Dr. Ping Li in the Department of Statistics and Biostatistics at Rutgers University. Then, he moved to the Department of Computer Science at Johns Hopkins University and worked as a Post-Doctoral Fellow under Dr. Suchi Saria together with Dr. Austin Reiter and Dr. Nishi Rawat (MD). Now, he is a Post-Doctoral Fellow in the Department of Computer Science at Hong Kong Baptist University, working on machine learning for liver disease diagnosis and precdition with Prof. Pong Chi Yuen, Prof. Grace LH Wong (MD), and Prof. Vincent WS Wong (MD).

Research Interest

Machine Learning, Computer Vision, Health Informatics

News & Upcoming Events

    • 1 paper accepted in Alimentary Pharmacology & Therapeutics, top 5% in pharmacology & pharmacy and top 12% in gastroenterology & hepatology, with impact factor 6.320
    • 1 paper published in Critical Care Medicine, top journal (rank 4) in critical care medicine, with impact factor 7.442

Selected Publications

    Journal

  1. Terry CF Yip1, Andy J Ma1, Vincent WS Wong, YK Tse, Henry LY Chan, Pong-Chi Yuen, and Grace LH Wong. Laboratory parameter-based machine learning model for non-alcoholic fatty liver disease (NAFLD) in the general population. Alimentary Pharmacology & Therapeutics, 2017. (Impact factor 6.320)
  2. Andy J Ma1, Nishi Rawat1, Austin Reiter, Christine Shrock, Alex Stone, Andong Zhan, Anahita Rabiee, Stephanie Griffin, Dale Needham, and Suchi Saria. Non-Invasive Sensor for Automatic Patient Mobility Measurement. Critical Care Medicine, vol. 45, no. 4, pp. 630–636, 2017. (Impact Factor: 7.442) [Link]
  3. Andy J Ma, Pong C Yuen, Jiawei Li and Ping Li. Cross-Domain Person Reidentification Using Domain Adaptation Ranking SVMs. IEEE Transactions on Image Processing (TIP), vol. 24, no. 5, pp. 1599-1613, 2015. (Impact Factor: 3.735) [PDF] [Project] [Code] [Results]
  4. Andy J Ma, Pong C Yuen. Reduced Analytic Dependency Modeling: Robust Fusion for Visual Recognition. International Journal of Computer Vision (IJCV), vol. 109, no. 3, pp. 233-251, 2014. (Impact Factor: 4.270) [PDF] [Project] [Code]
  5. Andy J Ma, Pong C Yuen, and Jian-Huang Lai. Linear Dependency Modeling for Classifier Fusion and Feature Combination. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 35, no. 5, pp. 1135-1148, 2013. (Impact Factor: 6.077) [PDF] [Project] [Code]
  6. Andy J Ma, Pong C Yuen , Weiwen Zou, and Jian-Huang Lai. Supervised Spatio-Temporal Neighborhood Topology Learning for Action Recognition. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), vol. 23, no. 8, pp. 1447-1460, 2013. (Impact Factor: 2.254) [PDF] [Project] [Code] [Data]
  7. ...

    Conference

  8. Andy J Ma, Pong C Yuen, and Jiawei Li. Domain Transfer Support Vector Ranking for Person Re-Identification without Target Camera Label Information. IEEE International Conference on Computer Vision (ICCV), 2013. [PDF]
  9. Andy J Ma and Pong C Yuen. Reduced Analytical Dependency Modeling for Classier Fusion. European Conference on Computer Vision (ECCV), 2012. [PDF] [Poster] [Spotlight]
  10. Andy J Ma and Pong C Yuen. Linear Dependency Modeling for Feature Fusion. IEEE International Conference on Computer Vision (ICCV), 2011. [PDF] [Poster] [Spotlight]
  11. ...

Academic Services

  • Associate Editor
    • Journal of Electronic Imaging
  • Reviewer
    • IEEE Transactions on Cybernetics
    • IEEE Transactions on Information Forensics and Security
    • Pattern Recognition
    • IEEE Transactions on Human-Machine Systems
    • Sensors
    • Optical Engineering