معرفی
Hyunseung Kang is an Associate Professor in the Department of Statistics at the University of Wisconsin-Madison, affiliated with the Department of Educational Psychology (Quantitative Methods), Department of Biostatistics and Medical Informatics (BMI), Center for Demography and Ecology (CDE), and Center for Demography of Health and Aging (CDHA). He completed his PhD in Statistics at the Wharton School (2015), with postdoctoral training at Stanford University (2015-2016).
Education:
- PhD in Statistics, University of Pennsylvania (2010-2015)
- MS in Statistics, Stanford University (2009-2010)
- Bachelor of Science in Mathematical and Computational Science, Stanford University (2006-2010)
Research: Focuses on causal inference methods using instrumental variables, econometrics, semi/nonparametric techniques, network analysis, and machine learning. Applications span genetics, epidemiology, health policy, education, and microeconomics. Recent grants include support from NSF, NIH, and UW-Madison initiatives.
Teaching: Teaches advanced courses like Causal Inference (Stat 992), emphasizing theoretical foundations and practical applications.
Software: Developed R packages like ivmodel for instrumental variables analysis, published in Observational Studies. Actively contributes to open-source tools for causal inference.
Awards: Recognized through grants and editorial roles, including Associate Editor for Biometrics and Journal of the American Statistical Association.
