Research Topic: Stochastic gradient descent for modeling non-proportional hazards with large-scale survival data; block steepest descent for integrating data with group feature selection data

Research Topic: Multi-view learning to assess drug response for psoriatic patients using multi-omics data

Research Topic: A joint model on clustered recurrent events; CUSUM for provider profiling with recurrent events

Research Topic: Kullback-Leibler-based relative risk models for integration of multiple data sources

Xiangeng has broad interests in developing statistical and computational methods with application in biomedical data. His current work mainly focuses on data integration, deep learning and survival analysis. Apart from studying, he enjoys doing sports, playing video games and watching movies.

Lingxuan’s research interests are developing dynamic treatment regimes for kidney transplantation using survival outcomes and standardization methods for evaluating medical center performances. In field s other than academic, he has motorcycle license and is good at cooking seafood.

Yu bo’s current research focuses on provider profiling, high - dimensional variable selection and survival analysis. In addition to research, he is also a big fan of soccer, a good photographer and a good cook.

Yuntian works on developing computational analysis pipelines, statistical methods, and computational approaches to provide biological inferences from genetics and genomics data.

Ruiwen is interested in applying statistical and computational methods to gain biological insights from varies biomedical data including microbiome and genetics data, as well as genome-wide association studies. In addition to his research work, he has a passion for classical music and enjoys playing the violin.