I am an Assistant Professor in the Graduate School of Data Science at Seoul National University. Prior to joining Seoul National University, I was an Associate Research Scientist at Columbia University and Postdoctoral Research Associate at Computer Science, Purdue University working with Prof. Elias Bareinboim. I got my Ph.D. in College of Information Sciences and Technology, Pennsylvania State University, University Park, under the supervision of Prof. Vasant Honavar.Currently, I am working on developing methods for applying causality in sequential decision-making and developing theory of causal effect identifiability and transportability. During my Ph.D. study, I focused on causal discovery in a relational domain.
- Causal Inference (how can we identify the effect of an intervention?), Causal Decision Making (how can we utilize causal information in decision making?), Causal Discovery (how can we establish causal relationships from complex data?)
- (Future) Developing theories and applications for health and social domains with causality as a first principle by bringing ideas from economics. Developing robust machine learning algorithms utilizing causal knowledge.
Employment & Education
|Seoul National University||Assistant Professor||2021—present|
|Columbia Univeristy||Associate Research Scientist||2019—2021|
|Purdue University||Postdoctoral Research Associate||2018—2019|
|Pennsylvania State University||Ph.D.||2013—2018|
- (Jul 2021) A paper on ‘counterfactual identification’ (joint work with Correa and Bareinboim) is online.
- (Mar 2021) I joined Graduate School of Data Science at Seoul National University as an Assistant Professor.
- (Sep 2020) A paper on exploring the optimal policy for structural causal bandits accepted at NeurIPS’20!
- (Aug 2020) Invited talk at CSE AIGS, POSTECH, South Korea
- (Jun 2020) A paper on identifiability with partial-observability is accepted at ICML’20.
- (Feb 2020) Attended AAAI’20 to present general identifiability and transportability papers.
- (Nov 2019) A paper on transportability is accepted at AAAI’20. Additionally, the GID paper is invited to a sister track.
- (Jul 2019) I am thrilled to announce that my paper on general identifiability won the best paper award at UAI’19.
- (Jul 2019) I am joining Columbia University as an Associate Research Scientist!
- (May 2019) Two papers are accepted at UAI’19.
Program Committee for
- 2022 ICLR
- 2021 ICLR, AAAI, AISTATS, UAI, ICML, NeurIPS, Journal of Artificial Intelligence Research
- 2020 NeurIPS, UAI, ICML, AAAI, AISTATS, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Journal of Artificial Intelligence (AIJ), Journal of Causal Inference (JCI), NeurIPS Workshop on Causal Discovery and Causality-Inspired Machine Learning (CDML, Area Chair)
- 2019 NeurIPS, WHY conference, Journal of Machine Learning Research (JMLR), 2017 Causality Workshop at UAI, 2016 ACM CHI, 2014 ACM Transactions on Intelligent Systems and Technology
- Yesong Choe (Ph.D. program 2021~)
- Yeahoon Kwon (Ph.D. program 2021~)
- Chaeyoung Chung (master program 2021~)
- Juhyeon Kim (master program 2021~)
- Taehan Kim (master program 2021~)
- Dong Kyu Cho (master program 2021~)
- Jewon Kang (master program 2021~)