Yuxin Wang 王语馨
I am a PhD student in Computer Science at LMU Munich, in the Institute of AI in Management, supervised by Prof. Dr. Stefan Feuerriegel. I am affiliated with the Munich Center for Machine Learning (MCML) and relAI (MCML). My research is in causal machine learning, semiparametric estimation, multi-fidelity Gaussian Process, with a growing focus on applications to LLM alignment and safety. More specifically, my research interests span:
- Semiparametric & debiased ML: efficient influence functions, doubly robust estimation, and Neyman-orthogonal methods for treatment effects
- Causal survival analysis: partial identification and CATE bounds for time-to-event outcomes under informative censoring
- Causal inference for LLM alignment: off-policy evaluation, policy learning, and safety from preference and observational data
- Applications in medicine and economics
News!
[06/18/2026] I am co-organizing the MCML Causal Machine Learning Workshop! Submissions are welcome.
[05/28/2026] Our paper Causal Methods for LLM Development and Evaluation got accepted at the KDD 2026 Blue Sky Track!
[05/13/2026] Received the ICML 2026 Gold Reviewer Award!
[02/26/2026] Gave a talk on Assessing the Robustness of Heterogeneous Treatment Effects in Survival Analysis under Informative Censoring at Tsinghua University, Beijing.
[09/10/2025] Our paper Assessing the Robustness of Heterogeneous Treatment Effects in Survival Analysis under Informative Censoring got accepted as an oral presentation at the CauScien Workshop of NeurIPS 2025!