The team’s work supports evidence-based decision making, informed by the models, to rethink and facilitate hospital operations in utilizing limited critical resources as demand surges.
Research Interests: Data science, statistics for big or high-dimensional data, simultaneous inference, multiple comparisons, selection bias, measurement errors, mixtures, causal inference, semi and nonparametric analysis, machine learning, biostatistics, random fields, crowdsourcing, EHR and Text analysis, the interface of statistics and computer science, and other interdisciplinary work.
Research Interests: Self-propelled nanoparticles, mechanobiology, extracellular matrix, microbiology, fluid dynamics, heat transfer
Research Interests: Health Informatics, public health informatics, mental health informatics, and computational social science
