Zhanghao Sun

I am a 5th year PhD student at Electrical Engineering, Stanford University. I work mainly in the field of computational imaging hardware and algorithms. I'm advised by Prof. Olav Solgaard, and co-advised by Prof. Gordon Wetzstein.

In Summer 2019, I worked as an algorithm engineer intern at Adaps, a startup that manufactures direct time-of-flight (dToF) sensors. In Summer 2021, I worked as a research intern at Snapchat, computational imaging team. In Summer 2022, I worked as a research intern at Meta Reality Labs, on-device computer vision team. I'm currently a part-time student reseacher in this team.

Email  /  CV  /  Google Scholar  /  Linkedin  /  Github

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Selected Publications
Consistent Direct Time-of-Flight Video Depth Super-Resolution
Zhanghao Sun, Wei Ye, Jinhui Xiong, Gyeongmin "Chris" Choe, Jialiang Wang, Shuochen Su, Rakesh Ranjan
CVPR, 2023
paper supplementary project code video

We propose algorithm and dataset for high accuracy, temporally consistent time-of-flight video depth super-resolution.

Energy-Efficient Adaptive 3D Sensing
Brevin Tilmon, Zhanghao Sun, Sanjeev Koppal, Yicheng Wu, Georgios Evangelidis, Ramzi Zahreddine, Guru Krishnan, Sizhuo Ma, Jian Wang
CVPR, 2023
project code

We propose energy-efficient and eye-safe active 3D sensor with parallel adaptive sampling.

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Seeing Far in the Dark with Patterned Flash
Zhanghao Sun, Jian Wang, Yicheng Wu, Shree Nayar
ECCV, 2022
paper supplementary poster code video

Our proposed novel flash pattern shows significantly better imaging quality at long distances in low-light environments.

Click to view difference
Structured Light with Redundancy Codes
Zhanghao Sun, Yu Zhang, Yicheng Wu, Dong Huo, Yiming Qian, Jian Wang
arXiv, 2022

We adopt redundancy coding from the communication system to improve the robustness of the structured light system.

Transparent Camera
Jian Wang*, Zhanghao Sun, Dejia Xu
ICCP, 2022   (Best Poster Award)

We proposed the transparent camera prototype with potential application in mobile devices.

Experimentally realized in situ backpropagation for deep learning in nanophotonic neural networks
Sunil Pai, Zhanghao Sun, Tyler W Hughes, Taewon Park, Ben Bartlett, Ian Williamson, Momchil Minkov, Maziyar Milanizadeh, Nathnael Abebe, Francesco Morichetti, Andrea Melloni, Shanhui Fan, Olav Solgaard, David Miller.
Science, 2023
paper code

For the first time, we realized neural network back-propagation in the optics (photonics) domain.

Resonant scanning design and control for fast spatial sampling
Zhanghao Sun, Ronal Quan, Olav Solgaard
Scientific Reports, 2021
CLEO (Oral), 2021
journal conference code

Fast, adaptive spatial sampling with resonant scanner for better machine perception and localization.

SPADnet: deep RGB-SPAD sensor fusion assisted by monocular depth estimation
Zhanghao Sun, David Lindell, Olav Solgaard, Gordon Wetzstein
Optics Express, 2020
paper project code

We propose a neural network solution to fuse monocular depth and metric depth from noisy dToF sensors.


Sandra Manosalvas-Kjono, Ronald Quan, Olav Solgaard, Zhanghao Sun. Method and apparatus for evaluating electrostatic or nonlinear devices , US11192779B2, 2021

Sandra Manosalvas-Kjono, Ronald Quan, Olav Solgaard, Zhanghao Sun. Method and apparatus for evaluating electrostatic or nonlinear devices , US20220089432A1, 2021


Teaching Assisant, ENGR240: Introduction to Micro and Nano Electromechanical Systems, Stanford University EE, 2020 2021

Website credits to Jon Barron