International Conference on Learning Representations · 2024
Cited
28
Resume (English only)
Academic Achievements
Published several papers, including 'Inside-out: Hidden Factual Knowledge in LLMs' (COLM 2025), 'LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations' (ICLR 2025), 'MIB: A Mechanistic Interpretability Benchmark' (ICML 2025), and more.
Research Experience
Currently a Research Fellow at the Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University. Previously worked at Microsoft for 3.5 years on AI solutions for cloud security and NLP applications for security-related problems.
Education
Completed B.Sc. and M.Sc. degrees at the Technion – Israel Institute of Technology and Ph.D. under the supervision of Yonatan Belinkov. Selected as a 2023 Apple Scholar in AI/ML.
Background
Research interests include the internals of AI, particularly how interpretability can be used to improve robustness, safety, and trustworthiness. Research problems involve hallucinations, bias, and unsafe outputs.
Miscellany
Passionate about AI interpretability and open to connecting with others for brainstorming or collaboration.