Chan Park
Chan Park
Contact
136 Computing Applications Building
605 E Springfield Ave
Champaign, IL 61820
E-mail : parkchan[at]illinois[dot]edu
Github : http://github.com/qkrcks0218
If you are a PhD student at UIUC interested in working with me, please contact me via email.
Background
Background
I am an assistant professor in the Department of Statistics at the University of Illinois Urbana-Champaign.
I am an assistant professor in the Department of Statistics at the University of Illinois Urbana-Champaign.
I was a postdoctoral researcher in the Department of Statistics and Data Science at the Wharton School, University of Pennsylvaina, mentored by Prof. Eric J. Tchetgen Tchetgen. In May 2022, I received my Ph.D. in Statistics from the University of Wisconsin-Madison where I was advised by Prof. Hyunseung Kang. Prior to joining the Ph.D. program in July 2017, I worked as a statistician for two and a half years at the Central Bank of Korea. I received a B.S. in Statistics from Seoul National University.
I was a postdoctoral researcher in the Department of Statistics and Data Science at the Wharton School, University of Pennsylvaina, mentored by Prof. Eric J. Tchetgen Tchetgen. In May 2022, I received my Ph.D. in Statistics from the University of Wisconsin-Madison where I was advised by Prof. Hyunseung Kang. Prior to joining the Ph.D. program in July 2017, I worked as a statistician for two and a half years at the Central Bank of Korea. I received a B.S. in Statistics from Seoul National University.
My research broadly focuses on (a) causal inference under interference and non-i.i.d. settings, (b) causal inference under unmeasured confounding, and (c) optimal treatment regimes and policy learning. A common theme in my research is to use non/semiparametric theory and optimization methods to develop efficient and robust estimators of causal quantities in (a)-(c).
My research broadly focuses on (a) causal inference under interference and non-i.i.d. settings, (b) causal inference under unmeasured confounding, and (c) optimal treatment regimes and policy learning. A common theme in my research is to use non/semiparametric theory and optimization methods to develop efficient and robust estimators of causal quantities in (a)-(c).
Employment
Employment
2024- Assistant Professor
Department of Statistics, University of Illinois Urbana-Champaign2022-2024 Postdoctoral Researcher
Department of Statistics and Data Science, University of Pennsylvania
Mentor: Professor Eric J. Tchetgen Tchetgen2015-2017 Statistician
the Central Bank of Korea
Education
Education
2017-2022 Ph.D. in Statistics
University of Wisconsin-Madison
Advisor: Associated Professor Hyunseung Kang2009-2015 B.S. in Statistics, minored in Economics
Seoul National University