Mark J. van der Laan is a Jiann-Ping Hsu/Karl E. Peace Professor of Biostatistics and Statistics at the University of California, Berkeley. His research concerns causal inference, prediction, adjusting for missing and censored data, and estimation based on high-dimensional observational and experimental biomedical and genomic data. He is the recipient of the 2005 COPSS Presidents' and Snedecor Awards, as well as the 2004 Spiegelman Award, and is a Founding Editor for the International Journal of Biostatistics.
Sherri Rose is an Associate Professor in the Department of Health Care Policy at Harvard Medical School. Her research interests include semiparametric estimation in causal inference and machine learning for prediction. She co-leads the Health Policy Data Science Lab at Harvard and is a 2017 NIH Director's New Innovator Award recipient. Dr. Rose has served on several editorial boards, including as associate editor for JASA-Theory & Methods, and is incoming co-editor of Biostatistics.
Both Targeted Learning books are unique in that they also contain wonderful contributions from multiple invited authors, yet are not traditional edited texts. As the authors, we spent significant time crafting and reworking each of the contributed chapters to have consistent style, content, format, and notation as well as a familiar road map. This yields truly cohesive books that each read easily as complete texts.