Caglar Gulcehre

Caglar Gulcehre is a Tenure Track Assistant Professor at École Polytechnique Fédérale de Lausanne (EPFL) and Principal Investigator of the CLAIRE (Caglar Gulcehre Laboratory of Artificial Intelligence Research) lab. Previously, he worked as a Staff Research Scientist at Google DeepMind, Microsoft Research, and IBM Research. His research focuses on reinforcement learning, foundation models, LLM alignment, and sequence modeling.

• Current Position: Assistant Professor, EPFL
• Lab: CLAIRE Lab
• Previous Roles: Staff Research Scientist at DeepMind, MSR, IBM Research

His work spans reinforcement learning, deep learning, and neural architecture design, with a focus on safety, trustworthy AI, and real-world applications. He has published in top venues including Nature, NeurIPS, ICML, and JMLR.

Scientific contributions include:

• Best paper award at NeurIPS Nonconvex Optimization workshop
• Honorable mention for best paper at ICML 2019
• Co-organizer of seven workshops at NeurIPS, ICML, and ICLR

He supervises PhD students in areas related to AI for algorithm discovery, neural architectures, and foundation models, including:

• Skander Moalla
• Justin Samuel Deschenaux
• Liangze Jiang
• Xiuying Wei
• Yitao Xu