معرفی
Cengiz Pehlevan is an Assistant Professor of Applied Mathematics at the Harvard School of Engineering and Applied Sciences (SEAS) and an Associate Faculty member at the Kempner Institute. His research bridges computational neuroscience, machine learning, and theoretical computer science.
Education:
- Ph.D. in Physics, Brown University
- B.S. in Physics and Electrical Engineering, Bogazici University
Pehlevan's work focuses on understanding learning dynamics in neural networks, neural scaling laws, feature learning, and biologically plausible learning mechanisms. His recent publications analyze the interplay between artificial and natural learning systems, emphasizing mathematical rigor.
Scientific Awards:
- Swartz Fellow
His research has been published in top venues, covering topics like reinforcement learning, kernel methods, and statistical physics of neural networks. He applies tools from theoretical physics and mathematics to machine learning challenges.
