# Ren Ng

### Research Areas

- Graphics (GR)
- Signal Processing (SP)
- Artificial Intelligence (AI)
- Imaging Systems; Computational Photography;
- Optics

### Research Centers

- Berkeley Artificial Intelligence Research Lab (BAIR)
- Visual Computing Lab (VCL)

### Teaching Schedule

#### Spring 2024

- CS 184. Foundations of Computer Graphics, TuTh 11:00-12:29, Dwinelle 145
- CS 284A. Foundations of Computer Graphics, TuTh 11:00-12:29, Dwinelle 145

## Biography

Ren Ng is a professor in Electrical Engineering and Computer Science at the University of California, Berkeley. His research interests are in imaging, graphics, computer vision, human vision and artificial intelligence. Prior to Berkeley, Ren was founder and CEO of Lytro, Inc., which commercialized his Ph.D. research and brought consumer light field cameras to market. Ren completed his Ph.D. in computer science at Stanford University, and received the ACM Doctoral Dissertation Award and Stanford's Arthur Samuel Award. Ren has received the 2020 ECCV Best Paper Honorable Mention, Jim and Donna Gray Faculty Award for Undergraduate Teaching, Hellman Faculty Fellowship, Sloan Research Fellowship, the HIPA Photographic Research Award, PMDA Technical Achievement Award, R.I.T.'s Imaging Hall of Fame, the Selwyn Award from the Royal Photographic Society, MIT Tech Review's TR35 and Entrepreneur of the Year, Fast Company's 100 Most Creative People in Business, and Silicon Valley Journal's 40 under 40.

Postdoc

- Congli Wang

PhD Students

- Hannah Doyle

- James Fong

- Leyla Kabuli

- Jessica Lee

- Erich Liang

- Utkarsh Singhal

- Matthew Tancik

PhD Alumni

- Grace Kuo

- Ben Mildenhall

- Pratul Srinivasan

- Xuaner Cecilia Zhang

- Nicholas Antipa

## Education

- 2006, Ph.D., Computer Science, Stanford University
- 2006, M.S., Computer Science, Stanford University
- 2001, B.S., Mathematical and Computational Science, Stanford University

## Selected Publications

- M. Tancik, B. Mildenhall, T. Wang, D. Schmidt, P. P. Srinivasan, J. T. Barron, and R. Ng, "Learned Initializations for Optimizing Coordinate-Based Neural Representations," in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
- M. Tancik, P. P. Srinivasan, B. Mildenhall, S. Fridovich-Keil, N. Raghavan, U. Singhal, R. Ramamoorthi, J. T. Barron, and R. Ng, "Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains," in Conference on Neural Information Processing Systems (NeurIPS), 2020.
- C. Zhang, J. T. Barron, Y. Tsai, R. Pandey, X. Zhang, R. Ng, and D. E. Jacobs, "Portrait Shadow Manipulation," in ACM SIGGRAPH, Vol. 39, 2020.
- B. Mildenhall, P. P. Srinivasan, M. Tancik, J. T. Barron, R. Ramamoorthi, and R. Ng, "NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis," in European Conference on Computer Vision (ECCV), 2020.
- M. Tancik, B. Mildenhall, and R. Ng, "StegaStamp: Invisible Hyperlinks in Physical Photographs," in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
- B. Mildenhall, P. P. Srinivasan, R. Ortiz-Cayon, N. K. Kalantari, R. Ramamoorthi, R. Ng, and A. Kar, "Local Light Field Fusion: Practical View Synthesis with Prescriptive Sampling Guidelines," ACM Trans. Graph., vol. 38, no. 4, pp. 29:1--29:14, July 2019.
- X. Zhang, V. Nguyen, D. Yao, Y. Zhang, K. Matzen, and R. Ng, "Synthetic Defocus and Look-Ahead Autofocus for Casual Videography," ACM Transactions on Graphics, vol. 38, July 2019.
- X. Zhang, Q. Chen, R. Ng, and V. Koltun, "Zoom to Learn, Learn to Zoom," in Conference on Computer Vision and Pattern Recognition, 2019.
- N. Antipa, P. Oare, E. Bostan, R. Ng, and L. Waller, "Video from stills: Lensless imaging with rolling shutter," IEEE International Conference on Computational Photography, May 2019.
- G. Kuo, N. Antipa, R. Ng, and L. Waller, "3D Fluorescence Microscopy with DiffuserCam," in Computational Optical Sensing and Imaging, Optical Society of America, 2018, pp. CM3E.3.
- P. P. Srinivasan, R. Garg, N. Wadhwa, R. Ng, and J. T. Barron, "Aperture Supervision for Monocular Depth Estimation," in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
- X. Zhang, R. Ng, and Q. Chen, "Single Image Reflection Separation With Perceptual Losses," in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
- B. Mildenhall, J. T. Barron, J. Chen, D. Sharlet, R. Ng, and R. Carroll, "Burst Denoising With Kernel Prediction Networks," in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
- N. Antipa, G. Kuo, R. Heckel, B. Mildenhall, E. Bostan, R. Ng, and L. Waller, "DiffuserCam: Lensless Single-Exposure 3D Imaging," Optica, vol. 5, no. 1, pp. 1--9, Jan. 2018.
- P. P. Srinivasan, T. Wang, A. Sreelal, R. Ramamoorthi, and R. Ng, "Learning to Synthesize a 4D RGBD Light Field from a Single Image," in IEEE International Conference on Computer Vision (ICCV), 2017, pp. 2262--2270.
- S. A. Cholewiak, G. D. Love, P. P. Srinivasan, R. Ng, and M. S. Banks, "ChromaBlur: Rendering Chromatic Eye Aberration Improves Accommodation and Realism," ACM Transactions on Graphics (TOG, SIGGRAPH Asia), vol. 36, no. 6, pp. 210, 2017.
- N. Antipa, S. Necula, R. Ng, and L. Waller, "Single-Shot Diffuser-Encoded Light Field Imaging," in 2016 IEEE International Conference on Computational Photography (ICCP), 2016, pp. 1--11.
- M. Levoy, R. Ng, A. Adams, M. Footer, and M. Horowitz, "Light Field Microscopy," ACM Transactions on Graphics (TOG, SIGGRAPH), vol. 25, no. 3, pp. 924--934, 2006.
- R. Ng, "Digital Light Field Photography," Stanford University, 2006.
- R. Ng, "Fourier Slice Photography," ACM Transactions on Graphics (TOG, SIGGRAPH), vol. 24, no. 3, pp. 735--744, 2005.

## Awards, Memberships and Fellowships

- Hellman Fellow, 2019
- Jim and Donna Gray Award for Excellence in Undergraduate Teaching of Computer Science, 2019
- Sloan Research Fellow, 2017
- MIT Tech Review Top 35 Innovators Under 35 (TR35), 2012
- MIT Tech Review Top 10 Breakthrough Technologies (TR10), 2012
- ACM Doctoral Dissertation Award, 2006