About Me

I am a Ph.D. student in the Department of Electrical and Computer Engineering at The University of Hong Kong (HKU), advised by Prof. Edmund Y. Lam. Prior to joining HKU, I received my M.S. degree in Bio and Brain Engineering from KAIST under the supervision of Prof. Mooseok Jang, and my B.Eng. degree from Sichuan University.

My research centers on perception: how imaging systems can sense and interpret their environments more efficiently and rapidly. I am interested in perception across spatial scales—from macroscopic scenes to microscopic structures—and across representations from 2D to 3D, drawing on event-based vision, computational photography, and computational microscopy. In the long term, I aspire to develop imaging instruments that can capture and recreate meaningful memories as rich, multidimensional experiences beyond conventional photographs and videos.

News

Sep 2026
Joined HKU ECE as a Ph.D. student under the supervision of Prof. Edmund Y. Lam.
Aug 2026
Our preprint, “Feature-domain Fourier ptychographic tomography with dark-field illumination,” became available on arXiv.
Aug 2026
Received my M.S. degree in Bio and Brain Engineering from KAIST under the supervision of Prof. Mooseok Jang.
Jul 2026
Our paper, “Beyond the weak-scattering limit: accurate Kramers–Kronig phase imaging of high-contrast reflective surfaces via pupil modulation,” was published in Journal of Physics: Photonics.
Oct 2025
Presented the poster “Robust Fourier ptychographic tomography via feature domain” at the SPIE Advanced Biophotonics Congress (SPIE ABC 2025).
Sep 2024
Started my M.S. studies in Bio and Brain Engineering at KAIST and joined the Mooo Research Group.
Jun 2024
Graduated from Sichuan University with a B.Eng. degree and received the First Prize for Outstanding Undergraduate Thesis.
Jan 2024
Our paper, “Fast scaled cylindrical holography based on scaled convolution,” was published in Displays.

Selected Publications

† Equal contribution · ✉ Corresponding author · Bold and underlined indicates my name.

Feature-domain Fourier ptychographic tomography framework
Feature-domain Fourier ptychographic tomography with dark-field illumination
Chao Tan, Fangrui Lu, Sechan Park, Hyeonseo Na, Chanseok Lee, Chang-Seok Kim, Jeesu Kim, Hwidon Lee, and Mooseok Jang
arXiv, 2026 [Paper]

Summary: Feature-domain optimization improves the robustness of dark-field Fourier ptychographic tomography and enables label-free, gigavoxel-scale 3D refractive-index imaging with millimeter-scale coverage and cellular-scale structural contrast.

Overview of uncertainty-aware Fourier ptychography
Uncertainty-aware Fourier ptychography
N. Chen†✉, Y. Wu†, Chao Tan, L. Cao, J. Wang✉, and E. Y. Lam✉
Light: Science & Applications, 2025 [Paper]

Summary: A physics-informed differentiable framework that jointly estimates the sample and system parameters, improving the robustness and fidelity of Fourier ptychographic reconstruction under experimental uncertainties.

Overview of Fourier ptychographic microscopy
Fourier ptychographic microscopy 10 years on: a review
F. Xu†, Z. Wu†, Chao Tan, Y. Liao, Z. Wang, K. Chen, and A. Pan✉
Cells, 2024 [Paper]

Summary: A comprehensive review of the first decade of Fourier ptychographic microscopy, spanning its theoretical foundations, system implementations, biomedical applications, three-dimensional imaging, and integration with deep learning.

Scaled cylindrical holography system
Fast scaled cylindrical holography based on scaled convolution
Chao Tan, J. Wang✉, Y. Wu, J. Zhou, and N. Chen
Displays, 2024 [Paper]

Summary: A scaled-convolution diffraction method that enables efficient and flexible cylindrical hologram generation beyond conventional height constraints, validated through optical experiments.

Holographic Maxwellian display based on spherical crown diffraction
Large field-of-view holographic Maxwellian display based on spherical crown diffraction
W. Zhang, J. Wang✉, Chao Tan, Y. Wu, Y. Zhang, and N. Chen
Optics Express, 2023 [Paper]

Summary: A spherical-crown diffraction model for holographic Maxwellian displays that expands the achievable field of view without introducing complex optical components.