Brian Chao

I'm a 3rd year PhD student at Stanford University working in the Stanford Computational Imaging Lab, advised by Prof. Gordon Wetzstein. I'm grateful to be supported by the NSF GRFP and the Stanford Graduate Fellowship.

My research focuses on computational imaging, displays, and physical optics, and how they can be combined with modern graphics and 3D-ML techniques (such as NeRF, 3DGS, etc) to create novel AR/VR experiences.

I've interned at Meta Reality Labs, where I worked on 3D reconstruction with Changil Kim.

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Research

Large Étendue 3D Holographic Display with Content-adpative Dynamic Fourier Modulation
Brian Chao, Manu Gopakumar, Suyeon Choi, Liang Shi, Jonghyun Kim, Gordon Wetzstein
ACM SIGGRAPH Asia, 2024

The novel combination of a multisource laser array and a dynamic Fourier amplitude modulator significantly improves holographic display Ă©tendue and light field hologram image quality.

Full-colour 3D Holographic Augmented-Reality Displays with Metasurface Waveguides
Manu Gopakumar*, Gun-Yeal Lee*, Suyeon Choi, Brian Chao, Yifan Peng, Jonghyun Kim, Gordon Wetzstein
Nature, 2024

A near-eye display design that pairs inverse-designed metasurface waveguides with AI-driven holographic displays to enable full-colour 3D augmented reality from a compact glasses-like form factor.

Holographic Parallax
Seong-Woo Nam, Dongyeon Kim, Suyeon Choi, Juhyun Lee, Siwoo Lee, Manu Gopakumar, Brian Chao, Gordon Wetzstein, Yoonchan Jeong
ACM SIGGRAPH Emerging Technologies, 2024

The inclusion of parallax cues in CGH rendering plays a crucial role in enhancing perceptual realism, and we show this through a live demonstration of 4D light field holograms.

Neural Holographic Displays for Virtual Reality
Brian Chao*, Suyeon Choi*, Manu Gopakumar*, Gun-Yeal Lee, Jonghyun Kim, Gordon Wetzstein
ACM SIGGRAPH Emerging Technologies, 2023

Live demonstration of state-of-the-art image quality, full-color, 3D, holographic VR near-eye displays that supports natural accommodation.

High Brighness Holographic Projection
Brian Chao, Manu Gopakumar, Suyeon Choi, Gordon Wetzstein
Optics Letters, 2023

A novel light-efficiency loss function, AI-driven CGH techniques, and camera-in-the-loop calibration greatly improves holographic projector brightness and image quality.

Time-Division Multiplexing Light Field Display With Learned Coded Aperture
Brian Chao*, Chang-Le Liu*, Homer H. Chen
IEEE Transactions on Image Processing, 2022

Using coded apertures and a learning-based light field display optimization pipeline to reproduce correct defocus blurs for better accommodation cues.

Robust Light Field Synthesis From Stereo Images With Left-Right Geometric Consistency
Brian Chao, Chang-Le Liu, Homer H. Chen
IEEE International Conference on Image Processing (ICIP), 2021

Leveraging geoemtric consistency in stereo images to synthesize high-quality light fields.

Self-Supervised Deep Learning for Fisheye Image Rectification
Brian Chao*, Pin-Lun Hsu*, Hung-yi Lee, Y.C. Frank Wang
IEEE Internation Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020

We propose an image-to-image translation algorithm based on generative adversarial networks that rectifies fisheye images without the need of paired training data.

scTIE: data integration and inference of gene regulation using single-cell temporal multimodal data
Yingxin Lin, Tung-Yu Wu, Xi Chen, Sheng Wan, Brian Chao, Jingxue Xin, Jean Y.H. Yang, Wing H. Wong Y.X. Rachel Wang,
Genome Research, 2023

Using optimal transport to infer regulatory relationships predictive of cellular state changes in single-cell temporal and multimodal data.


Website source code from here.