cv

Academic Interests

  • Pragmatic Causal Inference
    • Partial Identification
    • Practical Causal Learning
    • Amortized Causal Inference
    • Real-World Deployment

Experience

2025-

Assistant Professor

School of Information Sciences, University of Illinois Urbana-Champaign

2025-

Faculty Affiliate

Illinois Informatics, University of Illinois Urbana-Champaign

2025-

Faculty Affiliate

National Center for Supercomputing Applications, University of Illinois Urbana-Champaign

2021

Applied Scientist Intern

Amazon Causality Team

Education

2018-2025

Ph.D. in Computer Science

Purdue University

  • Advisor: Elias Bareinboim
  • Dissertation: Causal Data Science: Estimating Identifiable Causal Effects
2016

M.S. in Industrial and Systems Engineering

KAIST

2014

B.S. in Mathematical Sciences; B.A. in Business and Technology Management

KAIST

Teaching

Spring 2026

Instructor, IS 455: Database Design & Prototyping

University of Illinois Urbana-Champaign

2020-2025

Graduate Teaching Assistant

Purdue Computer Science

  • Foundations of Computer Science, AI Basics, Data Structures, Database Systems, Data Science Capstone, Software Testing, Data Mining, Artificial Intelligence

Academic Service

2026

Invited Session Organizer

INFORMS 2026 Annual Meeting, Decision Analysis Society cluster

  • Pragmatic Causal Inference for Decision Science: Robust Methods Under Imperfect Assumptions
ongoing

Reviewer

Journals and conferences in causal inference, statistics, and machine learning

Honors and Awards

2024
  • Top Reviewer, NeurIPS 2024
  • Graduate Teaching Award, Purdue Computer Science
2023
2022