
Empirical Processes and Statistical Reinforcement Learning
3 contributors - Hardback
£145.99
Shuangge Ma is Professor of Biostatistics at the Yale School of Public Health. He was a Ph.D. student of Prof. Kosorok at the University of Wisconsin and worked with him on semiparametric modeling, survival analysis, and empirical processes.
Eric B. Laber is the James B. Duke Distinguished Professor of Statistical Sciences and Biostatistics and Bioinformatics at Duke University. He is a fellow of the American Statistical Association and the International Statistical Institute, as well as the recipient of the Gottfried E. Noether Award, the Raymond J. Carroll Award, and the American Statistical Association Outstanding Application Award.
Yingqi Zhao received her PhD in Biostatistics from the University of North Carolina at Chapel Hill in 2012. She is currently a Professor at Fred Hutchinson Cancer Center. Her research focuses on statistical methodologies for precision medicine, dynamic treatment regimes, clinical trial design, real-world studies, and machine learning, with applications in cancer therapeutics and prevention and health care delivery for patients with complex type 2 diabetes. Her 2012 publication in the Journal of the American Statistical Association has been widely cited and has provided a foundation for subsequent research on biomarker-guided treatment and prevention strategies. Her work on decision-making for disease surveillance using electronic medical record data was recognized with the 2011 Best Paper in Biometrics Award. Her research has been supported by multiple awards from the National Institutes of Health (NIH), the Hope Foundation, and the Patient-Centered Outcomes Research Institute (PCORI).