<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Zhewen Hou | TZstats Convergence Lab | Tian Zheng, Columbia Stats</title><link>https://tz33cu.github.io/author/zhewen-hou/</link><atom:link href="https://tz33cu.github.io/author/zhewen-hou/index.xml" rel="self" type="application/rss+xml"/><description>Zhewen Hou</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Thu, 28 May 2026 00:00:00 +0000</lastBuildDate><image><url>https://tz33cu.github.io/author/zhewen-hou/avatar_hu_7f90bd485cbfc044.jpg</url><title>Zhewen Hou</title><link>https://tz33cu.github.io/author/zhewen-hou/</link></image><item><title>Machine Learning Workflows in Climate Modeling: Design Patterns and Insights from Case Studies</title><link>https://tz33cu.github.io/publication/zheng-machine-2025/</link><pubDate>Thu, 28 May 2026 00:00:00 +0000</pubDate><guid>https://tz33cu.github.io/publication/zheng-machine-2025/</guid><description/></item><item><title>Calibrating Geophysical Predictions under Constrained Probabilistic Distributions</title><link>https://tz33cu.github.io/publication/2025-12-03-hou-calibrating-geophysical-predictions/</link><pubDate>Mon, 01 Dec 2025 00:00:00 +0000</pubDate><guid>https://tz33cu.github.io/publication/2025-12-03-hou-calibrating-geophysical-predictions/</guid><description/></item><item><title>Spatiotemporal upscaling of sparse air-sea pCO2 data via physics-informed transfer learning</title><link>https://tz33cu.github.io/publication/2024-10-08-kim-spatiotemporal-upscaling-pco2/</link><pubDate>Tue, 08 Oct 2024 00:00:00 +0000</pubDate><guid>https://tz33cu.github.io/publication/2024-10-08-kim-spatiotemporal-upscaling-pco2/</guid><description/></item><item><title>NSF-STC: Learning the Earth with AI and Physics</title><link>https://tz33cu.github.io/project/external-leap/</link><pubDate>Fri, 22 Oct 2021 00:00:00 +0000</pubDate><guid>https://tz33cu.github.io/project/external-leap/</guid><description>&lt;p>Learning the Earth with Artificial Intelligence and Physics (LEAP) is an NSF Science and Technology Center (STC) launched in 2021. LEAP’s mission is to increase the reliability, utility, and reach of climate projections through the integration of climate and data science.&lt;/p>
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