Email Address: firstname.lastname@example.org
The majority of yafeng's work is to analyse real data with complex structures. The types of data include longitudinal data and functional data. As the size of the data is generally large, I am particularly interested in developing new algorithms or methods in the 'big data' environment. Previously I proposed a new variable selection algorithm for functional linear regression with scalar response and mixed scalar and functional covariates as the main chapter of my thesis. This was applied to the movement data analysis for stroke patients.
Selected PapersShi, J. Q. and Cheng, Y (2014)Gaussian Process Function Data Analysis - R Package GPFDA. Technical report.
School of Mathematics and Statistics, Newcastle University, UK :
Serradilla, J. Shi, J. Q., Cheng, Y., Morgan, G., Lambden, C. and Eyre, J (2014)Automatic Assessment of Upper Limb Function During Play of the Action Video Game, Circus Challenge: Validity and Sensitivity to Change. (The best paper winner in the IEEE 3rd International Conference on Serious Games and Applications for Health, held on Rio de Janeiro, Brazil, May 14-16,2014)
School of Mathematics & Statistics, Newcastle University, :
Shi, J.Q, Cheng, Y., Serradilla, J., Morgan, G., Lambden, C., Ford, G.A., Price, C., Rodgers,H,Cassidy, T., Rochester, L. and Eyre, J.A. (2013)Evaluating Functional Ability of Upper Limbs after Stroke Using Video Game Data.
Brain and Health Informatics Volume 8211 of the series Lecture Notes in Computer Science: 181-192 Springer