Yonghan Jung is a Ph.D. candidate in the Department of Computer Science at Purdue University, specializing in causal data science. He is a member of the CausalAI Lab led by Professor Elias Bareinboim at Columbia University. His research focuses on developing estimation frameworks for causal effects using modern machine learning methods, with particular emphasis on semiparametric causal effect estimation, debiased machine learning, and their applications in explainable AI and healthcare. Yonghan holds a Master's degree in Industrial & Systems Engineering from KAIST, Korea, and dual Bachelor's degrees in Mathematical Sciences and Business and Technology Management from the same institution. He has published over 11 first-authored papers in top-tier AI/ML venues, including NeurIPS, ICML, and AAAI.