URMC / Department of Biostatistics and Computational Biology
Department of Biostatistics and Computational Biology
Colloquia Schedule Masters & PhD Programs Consulting Services
Welcome to the home page of the Department of Biostatistics and Computational Biology, located in the School of Medicine and Dentistry at the University of Rochester! Our department has a long record of excellence in methodological and collaborative research and in the education of professionals in and users of statistics. The Department currently has 21 faculty with research interests spanning traditional biostatistics, stochastic modeling, bioinformatics and computational biology. Methodological research interests of the faculty include analysis of large-scale datasets (e.g., from high-throughput sequencing and imaging applications), Bayesian methods, causal inference, clinical trial design, dynamic treatment regimes, longitudinal data analysis, modeling and analysis of data derived from biological and social networks, nonparametric and semiparametric inference, order-restricted inference, smoothing techniques, statistical computing, stochastic modeling of complex cell systems, and survival analysis.
The Department offers masters and doctoral degrees and has an active postdoctoral program supported by research and and a NIEHS training grant. We have strong collaborative relationships with Anesthesiology, Biomedical Genetics, Cardiology, Center for Heath and Technology, Clinical and Cardiovascular Research Center, Environmental Medicine, Microbiology and Immunology, Neurology, Orthopedics, Pediatrics, Psychiatry, Public Health Sciences, the Wilmot Cancer Institute, and many other departments, centers and units throughout the School. We are also an important contributor to the University of Rochester Clinical & Translational Science Institute.
The Department also operates a fee-based consulting service staffed by faculty, research associates and assistants, programmers and graduate students that can provide assistance on topics ranging from advice on study design and analysis to complete data management.
Robert Strawderman, ScD
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