Li, Yang
Work Experience
2018 - , Professor
2013 - 2018,Associate Professor
2012 - 2013,Assistant Professor
Grants
- PI: “Split Questionnaire Design and Its Analytic Methods,” Key Research Founding of National Bureau of Statistics, 2019LD07, 2019-2021
- PI: “Large Scale Spatial Network Data Modeling and Applications,” Renmin University of China Research Branding Program, 15XNI011 (renewed), 2018-2020
- PI: “Study on Adaptive Balanced Split Questionnaire Design and Its Data Analytical Methodologies,” National Natural Science Foundation of China, 71771211, 2018-2021
- PI: “Development of Statistical Methods for Big Data in Biomedical Research,” Renmin University of China Research Branding Program, 15XNI011, 2015-2017
- PI: “Predictive Modeling for Structural Variable Selection,” National Natural Science Foundation of China Young Researcher Program, 71301162, 2013-2016
- PI: “Research on Marginalized Random Effect Model of Longitudinal Data,” Renmin University of China Research Program, 13XNF058, 2013-2015
- Co-PI: “COVID-19 and Migration Systems in Transition,” Worldwide Universities Network Special Grant Scheme, 2020-2021
- Co-PI: “The Establishment of Overall Evaluation Methodology for Physician-patient Co-Constructing Parallel Medical Record with the Embodiment of the Real Efficacy of Traditional Chinese Medicine,” National Natural Science Foundation of China, 81774146,
2018-2021
- Co-PI: “Platform Construction and Cohort Study on Disease of Large Blood Vessel,” National Key Research and Development Program of China, 2016YFC0900901, 2016-2020
- Co-PI: “Study on Innovative Designs and Statistical Methods in Clinical Trial,” National Natural Science Foundation of China, 11371366, 2014-2017
- Co-PI: “Research on Statistical Models of Complex Spatial-Temporal Data,” National Natural Science Foundation of China Young Researcher Program, 11301536, 2014-2016
Research Interest
Correlated Data Analysis, Complex Survey Methods, Model Selection and Uncertainty Evaluation, Latent Variable Modeling, Robust Statistics, Clinical Trial Design, Text Mining, Computational Statistics on Massive Data.