About
I work on mechanistic interpretability, focusing on how language models handle knowledge and process information. My research particularly investigates tricky situations such as conflicts between learned parametric knowledge and contextual knowledge, with the goal of mitigating hallucinations in large language models.
I enjoy building practical ML systems end‑to‑end: data, modeling, evaluation, and deployment, with a particular focus on understanding the internal mechanisms of neural networks.
Education
PhD, Natural Language Processing
Experience
PhD Researcher
Mechanistic interpretability; knowledge handling in language models; hallucination mitigation
Research Focus
Mechanistic Interpretability
Developing techniques to understand how language models process and integrate different sources of knowledge.
Knowledge Source Attribution
Investigating conflicts between learned parametric knowledge and contextual information to mitigate hallucinations.
Probing Techniques
Developing probing methodologies to understand model behavior and knowledge processing mechanisms.
Publications
Contact
The fastest way to reach me is via LinkedIn.