Dr. Samet Oymak

Biography

Samet Oymak is an Associate Professor at the University of Michigan, where he focuses on developing principled, empirically impactful artificial intelligence and machine learning methods. His research emphasizes the mathematical foundations of transformers, sequence modeling, capabilities in language models, core optimization, and statistical learning theory. He has contributed significantly to the field, engaging in areas such as language model reasoning, reinforcement learning, and trustworthy AI. Oymak's recent publications include significant papers presented at prestigious conferences like ICML and AAAI, showcasing his work on adaptive tuning in dynamic environments and token prediction mechanisms. He actively teaches and mentors students, fostering interest in AI reasoning research. Oymak has received multiple awards for his contributions to the field, reflecting his dedication to advancing theoretical and algorithmic foundations in machine learning and artificial intelligence.

Research Interests

Experience

Courses