معرفی
Jian Kang is a Professor and Associate Chair for Research at the University of Michigan School of Public Health, specializing in Biostatistics. His work focuses on developing advanced statistical methods for large-scale biomedical data, with applications to precision medicine, neuroimaging, and genomics.
- Education:
- PhD in Biostatistics, University of Michigan (2011)
- MS in Mathematics (Statistics), Tsinghua University (2007)
- BS in Statistics, Beijing Normal University (2005)
Research Interests include Bayesian nonparametric methods, deep learning for medical imaging, ultra-high-dimensional variable selection, and graphical models for network inference. His 2025-2023 publications demonstrate expertise in Bayesian hierarchical modeling, spatial statistics, and machine learning for healthcare.
Scientific Awards:
- Michigan SPH Excellence in Research Award (2025)
- ICSA President's Citation Award (2024)
- Statistics in Biopharmaceutical Research Best Paper (2023)
- Best Paper in Biometrics by IBS Member (2022)
- Fellow, American Statistical Association (2021)
Grants include NSF-IIS (2021-2025) for BCI statistical learning, NIGMS (2020-2022) for metabolomics biomarker selection, NIDA (2020-2025) for imaging data analysis, and NIMH (2014-2025) for multidimensional neuroimaging methods.
Labs and Teams develop Bayesian computational tools for neuroimaging and spatial transcriptomics, collaborating with institutions like Emory University and University of North Carolina.
