Thomas W. Chittenden, PhD, DPhil, PStat

Statistical Sciences

Dr. Chittenden is the founding director of the WuXi NextCODE Advanced Artificial Intelligence Research Laboratory. This initiative includes a number of deep learning and probabilistic programming projects aimed at furthering scientific understanding of human disease initiation and progression, knowledge that can be directly applied in innovative products for better care and medicine in a range of disease areas.

The principal focus of Dr. Chittenden’s work is the development and application of integrated systems biology models to investigate evolutionary factors of human disease. The broad objective is to understand how genetic variation and somatic mutation regulate aberrant gene activity and subsequent disease biology. To this end, Dr. Chittenden spent a year as a Visiting Research Scientist in the Department of Statistics at the University of Oxford, where he formulated a general strategy for constructing machine learning models by integrating a priori biological knowledge with multiple types of high-throughput genomic and phenotype data.

Dr. Chittenden is an Accredited Professional Statistician™ with the American Statistical Association. In addition to his position at WuXi NextCODE, he holds academic appointments at Boston Children’s Hospital, Harvard Medical School, and Massachusetts Institute of Technology, where he lectures on biostatistics and mathematical biology. Dr. Chittenden also serves as a Senior Consultant for the Research Computing Group at the Harvard Medical School, and as the Chief Statistical Sciences Advisor for the Global Strategic Initiatives and Planning Committee of the International Society for Philosophical Enquiry. He holds a PhD in Molecular Cell Biology and Biotechnology from Virginia Tech and a DPhil in Statistics from the University of Oxford. His multidisciplinary postdoctoral training includes experimental investigations in Molecular and Cellular Cardiology from the Dartmouth Medical School and Integrative Functional Genomics, Biostatistics, and Mathematical Biology from the Dana-Farber Cancer Institute and the Harvard School of Public Health.