Tian Gu, Ph.D. | Columbia Biostatistics #DataIntegration #DataScience

Dr. Gu‘s research focuses on developing novel statistical and machine-learning approaches that leverage large external data sources to improve precision health and disease risk prediction. Her work also extends to COVID-19 and health disparities, with a particular emphasis on utilizing multi-center and EHR-linked biobank data to enhance ...

Journal of the Royal Statistical Society Series B: Statistical Methodology … Characteristics associated with racial/ethnic disparities in COVID-19 outcomes in an academic health care system. JAMA...

Tian Gu is a Principal Investigator and Research Scientist at MIT. His primary research interests involve nano-/micro-optics, integrated photonics, and photonic materials, focusing on the areas of metasurface flat optics, optical phase change materials, photonic interconnection/packaging, on-chip spectroscopy, artificial intelligence ...

Dr. Tian Gu is an Assistant Professor of Biostatistics in the Mailman School of Public Health at Columbia University. She specializes in developing statistical methods and computational tools for data integration using advanced technologies such as transfer and federated learning.

I am a tenure-track Assistant Professor of Biostatistics at Columbia University Mailman School of Public Health and an affiliated member of the Columbia Data Science Institute. My research focuses on developing statistical methods and computational tools for data integration using advanced technologies such as transfer and federated learning.

Robust angle-based transfer learning in high dimensions. [2023 ASA Young Investigator Award] [Link] Gu T, Han Y, Duan R. 2024 -- Journal of the Royal Statistical Society: Series B (Statistical Methodology) 7. Enhancing genetic risk prediction through federated semi-supervised transfer learning with inaccurate electronic health. record data.

Working in the field of health data science, I am passionate in utilizing data integration and machine learning tools to improve the precision and efficiency of disease risk prediction. As my PhD thesis, I am developing efficient statistical tools to incorporate external information from big health science data into internal studies.

T. Gu, H. J. Kim, C. Rivero-Baleine, and J. Hu, "Reconfigurable metasurfaces towards commercial success." Nat. Photon. 17 , 48–58 (2023). Jost, N., Gu, T., Hu, J., Domínguez, C. and Antón, I., “Integrated Micro-Scale Concentrating Photovoltaics: A Scalable Path Toward High-Efficiency, Low-Cost Solar Power.”