(734) 764-9328
Applications: Behavioral Science, Business Analytics, Children and Adolescents, Clinical Research, Environmental Sciences, Epidemiology, Finance Research, Human Development, Human Subjects Trials and Intervention Studies, Precision Health Methodologies: Algorithms, Data Management, Decision Science, Deep Learning, Heterogeneous Data Integration, High-Dimensional Data Analysis, Longitudinal Data Analysis, Machine Learning, Network Analysis, Optimization, Spatio-Temporal Data Analysis, Statistical Inference, Statistical Modeling, Tensor Analysis, Time Series Analysis Relevant Projects:



Big Data Panel, National Science Foundation

Peter X. K. Song

Professor, Biostatistics

Dr. Song interested in the development and application of theories and methodologies from Data Science to solve scientific problems arising from medical and public health sciences, in particular from the fields of environmental health sciences and nutritional sciences. People from his lab are strongly interested in interdisciplinary research in the areas of statistics, operation research, and machine learning, with the core interest in the statistical foundation of big data analytics, and with target applications in processing and analyzing big data from various applied sciences, including asthma, environmental health sciences, nephrology, and nutritional sciences. His research projects have been funded by NIH, NSF and DARPA funding agencies. Visit Song Lab webpage for detail: http://www.umich.edu/~songlab/