I am a PhD candidate in the Department of Electrical Engineering at Caltech, advised by Prof. Changhuei Yang. My current research interests include: (a) Computational microscopy - empowering imaging techqniues with algorithms;
(b) Synergizing microscopy, computation and artificial intelligence to advance life science.
News
06/04/2025 - I delivered an invited talk in ESE Seminar Series at Washington University in St. Louis, titled "Empowering microsopes with physics-based computation" [Talk page]
04/30/2025 - I delivered an invited talk in Computer Vision Seminar Series at University of Maryland, College Park, titled "Syngergizing microscopy and computation to advance life science research"
02/25/2025 - Check out our new paper "Single-shot volumetric fluorescence imaging with neural fields" on Advanced Photonics [paper link]
12/03/2024 - I am awarded Schmidt Academy for Software Engineering Graduate Research Fellowship. The support will start on Jan. 2025 for contributions to the algorithm and software development towards computational microscopy, specifically Fourier Ptychographic Microscopy. [Schmidt Academy GRA Fellows]
08/06/2024 - Our new paper titled "Investigating 3D microbial community dynamics of the rhizosphere using quantitative phase and fluorescence microscopy" is online at PNAS . [Science.org News]
05/24/2024 - I am awarded SPIE Optics and Photonics Scholarship . [Webpage] [PDF] [News]
03/06/2024 - The new paper "AI-guided histopathology predicts brain metastasis in lung cancer patients" has been featured on the Caltech homepage. News
03/04/2024 - My new paper on "AI-guided histopathology predicts brain metastasis in lung cancer patients" is online today. Check my publication list here !
02/14/2024 - I passed my candidacy exam!
11/21/2023 - My personal homepage is online!
06/30/2021 - I joined Caltech Biophotonics Lab!
Selected Publications
Full publication list here. Clicking paper titles will direct to the preprint or paper page.
Digital defocus aberration interference for automated optical microscopy
Haowen Zhou*, Shi Zhao*, Yujie Fan, Zhenyu Dong, Oumeng Zhang, Viviana Gradinaru, Changhuei Yang
arXiv, 2025 (BibTex) [Project Page & Code] {Data}
We recently discovered a phenomenon that the digitally summed Fourier spectrum of two images acquired from two-angle illumination exhibits interference-like fringe modulation when the sample is out-of-focus. These digital fringes correlate directly with defocus through a physics-based relation. Based on this principle, we developed an automatic, efficient, and generalizable defocus detection method termed digital defocus aberration interference (DAbI).
Haowen Zhou*, Shi Zhao*, Yujie Fan, Zhenyu Dong, Oumeng Zhang, Viviana Gradinaru, Changhuei Yang
arXiv, 2025 (BibTex) [Project Page & Code] {Data}
We recently discovered a phenomenon that the digitally summed Fourier spectrum of two images acquired from two-angle illumination exhibits interference-like fringe modulation when the sample is out-of-focus. These digital fringes correlate directly with defocus through a physics-based relation. Based on this principle, we developed an automatic, efficient, and generalizable defocus detection method termed digital defocus aberration interference (DAbI).
Analytic Fourier ptychotomography for volumetric refractive index imaging
Zhenyu Dong*, Haowen Zhou*, Ruizhi Cao*, Oumeng Zhang, Shi Zhao, Panlang Lyu, Reinaldo E Alcalde, Changhuei Yang
arXiv, 2025 (BibTex) [Project Page & Code] {Data}
We propose Fourier Ptychotomography (AFP), a new computational microscopy technique that analytically reconstructs aberration-free, complex-valued 3D RI distributions without iterative optimization or axial scanning. AFP incorporates a new concept named finite sample thickness (FST) prior, thereby simplifying the inverse scattering problem into solving linear equations.
Zhenyu Dong*, Haowen Zhou*, Ruizhi Cao*, Oumeng Zhang, Shi Zhao, Panlang Lyu, Reinaldo E Alcalde, Changhuei Yang
arXiv, 2025 (BibTex) [Project Page & Code] {Data}
We propose Fourier Ptychotomography (AFP), a new computational microscopy technique that analytically reconstructs aberration-free, complex-valued 3D RI distributions without iterative optimization or axial scanning. AFP incorporates a new concept named finite sample thickness (FST) prior, thereby simplifying the inverse scattering problem into solving linear equations.
Single-shot volumetric fluorescence imaging with neural fields
Oumeng Zhang*, Haowen Zhou*, Brandon Y Feng, Elin M Larsson, Reinaldo E Alcalde, Siyuan Yin, Catherine Deng, Changhuei Yang
Advanced Photonics, 2025 (BibTex) [Project Page & Code] {Data}
Single-shot volumetric fluorescence (SVF) imaging captures biological processes with high temporal resolution and a large field of view, unlike traditional methods requiring multiple axial plane scans. Existing SVF methods often face limitations due to large, complex point spread functions (PSFs), affecting signal-to-noise ratio, resolution, and field of view. The paper introduces a QuadraPol PSF combined with neural fields, using a compact custom polarizer and a polarization camera to detect fluorescence and encode the 3D scene within a compact PSF without depth ambiguity.
Oumeng Zhang*, Haowen Zhou*, Brandon Y Feng, Elin M Larsson, Reinaldo E Alcalde, Siyuan Yin, Catherine Deng, Changhuei Yang
Advanced Photonics, 2025 (BibTex) [Project Page & Code] {Data}
Single-shot volumetric fluorescence (SVF) imaging captures biological processes with high temporal resolution and a large field of view, unlike traditional methods requiring multiple axial plane scans. Existing SVF methods often face limitations due to large, complex point spread functions (PSFs), affecting signal-to-noise ratio, resolution, and field of view. The paper introduces a QuadraPol PSF combined with neural fields, using a compact custom polarizer and a polarization camera to detect fluorescence and encode the 3D scene within a compact PSF without depth ambiguity.
AI-guided histopathology predicts brain metastasis in lung cancer patients
Haowen Zhou*, Mark Watson*, Cory T. Bernadt, Steven (Siyu) Lin, Chieh-yu Lin, Jon H. Ritter, Alexander Wein, Simon Mahler, Sid Rawal, Ramaswamy Govindan, Changhuei Yang, Richard J. Cote
Journal of Pathology, 2024 (BibTex) [Code] {Data} News
Brain metastases can occur in nearly half of patients with early and locally advanced (stage I–III) non-small cell lung cancer (NSCLC). There are no reliable histopathologic or molecular means to identify those who are likely to develop brain metastases. We sought to determine if deep learning could be applied to routine H&E-stained primary tumor tissue sections from stage I–III NSCLC patients to predict the development of brain metastasis.
Haowen Zhou*, Mark Watson*, Cory T. Bernadt, Steven (Siyu) Lin, Chieh-yu Lin, Jon H. Ritter, Alexander Wein, Simon Mahler, Sid Rawal, Ramaswamy Govindan, Changhuei Yang, Richard J. Cote
Journal of Pathology, 2024 (BibTex) [Code] {Data} News
Brain metastases can occur in nearly half of patients with early and locally advanced (stage I–III) non-small cell lung cancer (NSCLC). There are no reliable histopathologic or molecular means to identify those who are likely to develop brain metastases. We sought to determine if deep learning could be applied to routine H&E-stained primary tumor tissue sections from stage I–III NSCLC patients to predict the development of brain metastasis.
FPM-INR: Fourier ptychographic microscopy image stack reconstruction using implicit neural representations
Haowen Zhou*, Brandon Y. Feng*, Haiyun Guo, Siyu Lin, Mingshu Liang, Christopher A. Metzler, Changhuei Yang
Optica, 2023 (BibTex) [Project Page & Code] {Data}
Fourier ptychographic microscope images the biological samples with high-resolution and large field-of-view simultaneously. However, this microscope faces challenges with long image stack reconstruction time and huge data volumes. We designed physics-based neural signal representations to tackle these challenges and showed potential in facilitating remote diagnosis, digital pathology, and efficient clinical data packaging.
Haowen Zhou*, Brandon Y. Feng*, Haiyun Guo, Siyu Lin, Mingshu Liang, Christopher A. Metzler, Changhuei Yang
Optica, 2023 (BibTex) [Project Page & Code] {Data}
Fourier ptychographic microscope images the biological samples with high-resolution and large field-of-view simultaneously. However, this microscope faces challenges with long image stack reconstruction time and huge data volumes. We designed physics-based neural signal representations to tackle these challenges and showed potential in facilitating remote diagnosis, digital pathology, and efficient clinical data packaging.
