I am a PhD researcher in the Artificial Intelligence group at the Hasso Plattner Institute (HPI), advised by Prof. Gerard de Melo, and currently a visiting researcher at Stanford University. My research centers on epistemic uncertainty and metacognition in large language models - building methods that let models recognize, quantify, and express the limits of their own knowledge, and studying how they reason about what they know. This spans factuality and hallucination reduction, calibrated abstention, knowledge editing, interpretability, and reasoning, across pretraining, alignment, and inference.

I am currently working on a few new projects and am open to collaborations. If your interests overlap with mine, please feel free to get in touch.

Research Interests

• Epistemic uncertainty and metacognition in LLMs
• Factuality and hallucination in LLMs
• Reasoning and interpretability
• Knowledge in language models - knowledge editing, internal knowledge bases
• Alignment and instruction tuning
• LLM safety

News / Updates

• 2026 - Began a visiting research position at Stanford University, August.
• 2025 - InFact: Informativeness Alignment for Improved LLM Factuality accepted to Findings of EMNLP 2025.
• 2025 - Featured in The Wall Street Journal on why AI chatbots struggle to admit “I don’t know.”
• 2024 - I Don’t Know: Explicit Modeling of Uncertainty with an [IDK] Token accepted to NeurIPS 2024.
• 2024 - Evaluating the Ripple Effects of Knowledge Editing in Language Models published in TACL.