Yuchen Ma 马羽宸
I am a Ph.D. student in Computer Science at LMU Munich and the Munich Center for Machine Learning (MCML), supervised by Prof. Stefan Feuerriegel. Before that, I received my M.Sc. in Mathematics & Computer Vision from Heidelberg University.
Currently, I am a research intern at Microsoft Research in Seattle, working with Swadheen Shukla and Michel Galley on LLM agents.
My research interests are in agentic AI, large language models, and causal inference. Specifically, I build causal foundation models, develop scalable methods for personalizing LLMs, study how LLM agents can distill verified, reusable skills, and explore how multiple agents interact and collaborate. I'm happy to connect and discuss potential collaborations.
News
Selected Projects
Agent Harness
We study how LLM agents can distill their own experience into reusable, verified skills that improve capabilities without retraining.
Highlights:
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SkillGen: Verified Inference-Time Agent Skill Synthesis, Preprint (💻 Code)
Other related works: NARRA-Gym for Evaluating Interactive Narrative Agents (Preprint)
Applicable and Reliable LLMs
We develop scalable approaches for adapting LLMs to individual users' preferences and latent constraints.
Highlights:
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Synthetic Interaction Data for Scalable Personalization in Large Language Models, In KDD 2026 (💻 Code)
Other related works: ProbeLLM (ICML'26), Treatment Effects under Text Confounding (NeurIPS'25)
Causal Foundation Models
We build foundation models that perform causal inference on new datasets in a training-free way via in-context learning.
Highlights:
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Foundation Models for Causal Inference via Prior-Data Fitted Networks, In ICLR 2026 (🧰 CausalFM Toolkit)
Other related works: DiffPO (NeurIPS'24), Multi-Outcome Distributions of Treatments (KDD'25), Treatment Effects under Text Confounding (NeurIPS'25), Counterfactual Fairness (CLeaR'26)
Recent Preprints & Publications
* = Equal contribution. The full publication list can be found on my Google Scholar profile.
Education
Experience
