Published multiple papers such as 'Apertus: Democratizing Open and Compliant LLMs for Global Language Environments', 'TiMoE: Time-Aware Mixture of Language Experts', 'URLs Help, Topics Guide: Understanding Metadata Utility in LLM Training', 'Can Performant LLMs Be Ethical? Quantifying the Impact of Web Crawling Opt-Outs', etc. Won oral presentation award at COLM 2025.
Research Experience
Involved in multiple research projects, including Apertus team's pretraining work, TiMoE: Time-Aware Mixture of Language Experts, URLs Help, Topics Guide: Understanding Metadata Utility in LLM Training, etc.
Education
4th-year PhD student at Machine Learning and Optimization Lab at EPFL, supervised by Prof. Martin Jaggi.
Background
Research interests include: Data-Efficient Language Modeling, Mixture-of-Experts architectures, Decentralized training methods, Accelerating LLM pretraining through metadata conditioning, Responsible Language Modeling, Data-compliant pretraining by respecting owners’ opt-out choices, Designing compensation frameworks for data contributors, Understanding and mitigating model hallucinations.
Miscellany
Likes arts and cultural stuff, enjoys outdoor activities like hiking, skiing, and sailing. Also paints from hiking trips.