Cross-Patch Dense Contrastive Learning for Semi-Supervised Segmentation of Cellular Nuclei in Histopathologic Images
Learning from fewer annotated cells, with contrastive signals across patches and pixels.
Computer vision · VLMs · Embodied AI
Hi, I'm Ciuzaak Wong. I work on computer vision and how it carries over to the physical world, from perception and vision-language models to synthetic data and embodied agents. Along the way, I build small tools for whatever gets in the way.
V toggles vision mode ⌘K for everything else
01Research interests
One apartment, four ways to understand it. Generate a home, inspect what is in it, reveal its collision geometry, then send a robot exploring.
02Trajectory
Drag the playhead. The main line is research; the dots underneath are side quests.
03Workshop
Public projects, with GitHub stats refreshed hourly.
04Publications
Earlier work on learning to see: from biomedical images to the textures of an illustration.
Papers published as Zhaoze Wang.
Saved snapshot
Learning from fewer annotated cells, with contrastive signals across patches and pixels.
Continuing to learn nuclei segmentation while preserving previously learned knowledge.
Context priors connect global semantics with the fine detail needed for biomedical segmentation.
Efficient multi-scale attention for precise polyp segmentation.
Finding textures that fit an illustration and work together as a coherent visual style.
Sync attempted daily. If Scholar blocks access, the last successful snapshot stays visible. Years follow Scholar; META-Unet appeared online in 2023 and in the 2024 journal issue.
05Off the clock
Some things are better built just for the fun of it. A miniature corner of my world: code, coffee, a curious robot, and a cat with management privileges.

Drag to look around. A small world, made by hand.
Blender × Three.js06Shell
A tiny terminal. Try one of these, or type help.
07Contact
Questions, collaborations, or unlikely ideas are all welcome.
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