Peyman is a Distinguished Scientist at Google, where he leads the Computational Imaging team. Prior to this, he was a Professor of Electrical Engineering at UC Santa Cruz for 15 years, two of those as Associate Dean for Research. From 2012-2014 he was on leave at Google-x, where he helped develop the imaging pipeline for Google Glass.

Over the last decade, Peyman's team at Google has developed several core imaging technologies that are used in many products. Among these are the zoom pipeline for the Pixel phones, which includes the multi-frame super-resolution (Super Res Zoom) pipeline, and several generations of state of the art digital upscaling algorithms.  Most recently, his team led the development of Unblur, and Zoom Enhance features launched in Google Photos and Pixel devices.

Peyman received his undergraduate education in electrical engineering and mathematics from the UC Berkeley, and the MS and PhD degrees in electrical engineering from MIT. He holds more than two dozen patents. He founded MotionDSP, which was acquired by Cubic Inc.

Along with his students and colleagues, his research work has had deep impact in several areas of computational imaging, and applications of AI thereto - including the introduction of adaptive kernel regression to imaging; pioneering use of learning for fast, content-adaptive image upscaling (RAISR); Neural Image quality Assessment (NIMA), Regularization by Denoising (RED); and most recently (2024) Inversion by Direct Iteration (InDI).  All of these works have been recognized with best paper awards. 

He's been a Distinguished Lecturer of the IEEE Signal Processing Society, and is a Fellow of the IEEE "for contributions to inverse problems and super-resolution in imaging"

New: Our work InDI has been awarded as one of two Outstanding Papers by the Transactions on Machine Learning Research!

Blog post of announcement (excerpt below)

Link to paper (TMLR)

Link to 15 min talk (YouTube)


@article{delbracio2023inversion,title={Inversion by Direct Iteration: An Alternative to Denoising Diffusion for Image Restoration},author={Mauricio Delbracio and Peyman Milanfar},journal={Transactions on Machine Learning Research},issn={2835-8856},year={2023},url={https://openreview.net/forum?id=VmyFF5lL3F},note={Featured Certification}}