Haowen Zhou
Ph.D. Student at UCSD. La Jolla, CA.

Acadia National Park
Maine, USA
I am Haowen Zhou, a first year Ph.D. student in the Bioinformatics and Systems Biology (BISB) program at UC San Diego, under the guidance of Dr. Neil C. Chi. My research is rooted in developing explicable and scalable computational approaches to advance integrative multi-modal biological data analysis. I am passionate about creating scalable and robust tools to uncover biological insights from high-dimensional multi-omics datasets.
Prior to my doctoral studies, I earned my M.S. in Bioinformatics from Johns Hopkins University, where I worked in Dr. Stephanie Hicks’ lab on scalable clustering methods (SpatialMNN) for multi-sample SRT data. I completed my B.S. in Bioscience from Shanghai Jiao Tong University through the prestigious Zhiyuan Honors Program, where I developed a strong foundation in computational biology, genomics, and molecular biology. My undergraduate thesis involved developing advanced computational tools to analyze multi-modality spatial data under the mentorship of Dr. Xiao Wang and Dr. Jing Li.
News
Jul 29, 2025 |
Thrilled to share our new paper spatialMNN on Bioinformatics! It’s a fast, scalable, and accurate method to integrate multiple spatial transcriptomics (SRT) datasets and identify shared spatial domains. Many thanks to for the amazing team behind spatialMNN! Thank you to my brilliant co-authors Pratibha Panwar, Boyi, and Caleb. And to our to our mentors, Shila and Stephanie for their incredible guidance and support. |
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Dec 19, 2024 | Deployed my first personal academic site! |
Latest posts
Feb 12, 2025 | SCENIC+ Tutorial |
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Dec 20, 2024 | ECE 271A Statistical Learning I Note |
Oct 20, 2015 | a post with disqus comments |
Selected publications
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Nat. Neurosci.Integrative in situ mapping of single-cell transcriptional states and tissue histopathology in a mouse model of Alzheimer’s diseaseNature Neuroscience, 2023
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Nat. MethodsSpatiotemporally resolved transcriptomics reveals the subcellular RNA kinetic landscapeNature Methods, 2023