I received my medical degree from China Medical University in 2010 with a focus on oncology and PhD in Biostatistics from University at Buffalo in 2018. In addition to methodological research, I also acquired extensive experience in collaboration with clinicians, epidemiologists and biologists during my PhD study, which involves the application of novel statistical methods in a variety of research projects. With an interdisciplinary background, I am familiar with the research techniques in biomedical sciences. I am also one of the top performers in an international data science competition on proteogenomics.
My research interest is in the development and application of novel statistical learning approaches in clinical and genomic studies, especially in areas related to precision medicine. The specific topics of my research interest include graphical models, high dimensional data analysis, variable selection, clustering analysis, survival analysis, and their applications. My current research concerns the utilization of network information to facilitate the identification of genomic characteristics associated with patients’ clinical outcomes or related phenotypes.
Han Yu, Brian Chapman, Arianna DiFlorio, Ellen Eischen, David Gotz, Matthews Jacob, Rachael Hageman Blair. Bootstrapping estimates of stability for clusters, observations and model selection. Computational Statistics. 2018; 1-24.
Brian Clemency, William Eggleston, Evan Shaw, Michael Cheung, Nicholas Pokoj, Michael Manka, Donald Giordano, Laura Serafin, Han Yu, Heather Lindstrom, David Hostler. Hospital Observation Upon Reversal (HOUR) with Naloxone: A Prospective Clinical Prediction Rule Validation Study. Academic Emergency Medicine. (Accepted)
Hangchuan Shi, Han Yu, Joaquim Bellmunt, Jeffrey J Leow, Xuanyu Chen, Changcheng Guo, Hongmei Yang, Xiaoping Zhang. Comparison of health-related quality of life (HRQoL) between ileal conduit diversion and orthotopic neobladder based on validated questionnaires: a systematic review and meta-analysis. Quality of Life Research. 2018; 1-17.
Han Yu, Rachael Hageman Blair. A framework for attribute-based community detection with applications to integrative functional genomics. Pacific Symposium on Biocomputing. 21:69-80(2016).
Han Yu, Yan Xin. Down-regulated expressions of PPARgamma and its coactivator PGC-1 are related to gastric carcinogenesis and Lauren's classification in gastric carcinoma. Chin J Cancer Res. 2013; 25(6):704-14.