Advanced Statistical Methods in Data Science / ICSA Book Series in Statistics (PDF)

Professor Ding-Geng Chen is a fellow of the American Statistical Association and currently the Wallace Kuralt distinguished professor at the University of North Carolina at Chapel Hill. He was a professor at the University of Rochester and the Karl E. Peace endowed eminent scholar chair in biostatistics at Georgia Southern University. He is also a senior statistics consultant for biopharmaceuticals and government agencies with extensive expertise in clinical trial biostatistics and public health statistics. Professor Chen has written more than 100 referred professional publications and co-authored and co-edited seven books on clinical trial methodology, meta-analysis and public health applications and he has been invited nationally and internationally to give presentations on his research. In 2014 Professor Chen received the "Award of Recognition" from the Deming Conference Committee for his contribution to highly successful advanced biostatistics workshop tutorials with his books. In 2013, he was invited to give a short course at the twentieth Annual Biopharmaceutical Applied Statistics Symposium (BASS XX, 2013) for his contribution in meta-analysis and received a "Plaque of Honor" for his short course. 
Professor Jiahua Chen is a Canada Research Chair, Tier I at the Department of Statistics, University of British Columbia. He has made important and fundamental research contributions to the theory and application of mixture models, empirical likelihood, variable select, the theory of sampling and the design of experiments. He has published over 100 research papers. He is the elected fellow of the Institute of Mathematical Statistics and the American Statistical Association. He was the recipient of the Gold Medal of the Statistical Society of Canada in 2014.
Xuewen Lu is Professor of Statistics at the University of Calgary. His broad research interest lies in the areas of biostatistics, predictive microbiology models, survival analysis, theory of semiparametric

“This handbook has a good collection of material on useful and interesting topics on data science. The book will be useful to graduate students and researchers interested in gaining perspectives and knowledge on this useful topic. The book comprises a wealth of information, a one-stop shopping, and can be served as a research reference book.” (Technometrics, Vol. 59 (2), April, 2017)