Cengiz Pehlevan

Cengiz Pehlevan is an Associate Professor of Applied Mathematics at Harvard University's John A. Paulson School of Engineering and Applied Sciences. His primary teaching area is Applied Mathematics. Pehlevan's research interests include computational neuroscience, computational science and engineering, data science, machine learning, and artificial intelligence. He is affiliated with the Pehlevan Group and can be contacted via email at cpehlevan@seas.harvard.edu. His work has been recognized through awards such as the NSF CAREER Award and Sloan Research Fellowships.

Cengiz Pehlevan is a researcher at Harvard University with expertise in Neural Networks, Theoretical Neuroscience, Machine Learning, and the Physics of Learning. His work explores the interplay between neural systems and computational models, focusing on how biological and artificial neural networks learn and generalize. Pehlevan's research includes topics such as kernel regression, spectral bias, and the dynamics of neural scaling laws. He investigates how neural circuits process information and how learning mechanisms can be modeled using mathematical frameworks. His publications address the theoretical foundations of machine learning and their applications to neuroscience, emphasizing the role of kernel methods, spectral properties, and learning dynamics in both biological and artificial systems.