<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Company | Hao Yan</title><link>https://hyan46.github.io/tag/company/</link><atom:link href="https://hyan46.github.io/tag/company/index.xml" rel="self" type="application/rss+xml"/><description>Company</description><generator>Wowchemy (https://wowchemy.com)</generator><language>en-US</language><copyright>© 2026 Hao Yan</copyright><lastBuildDate>Thu, 19 Mar 2020 00:00:00 +0000</lastBuildDate><image><url>https://hyan46.github.io/media/icon_hudffdcafa99c609c7e4dfde01dba38f93_35970_512x512_fill_lanczos_center_3.png</url><title>Company</title><link>https://hyan46.github.io/tag/company/</link></image><item><title>Procter &amp; Gamble Company, Modeling Multi-Stage Manufacturing Processes and Related Problems</title><link>https://hyan46.github.io/project/ai-manufacturing/</link><pubDate>Thu, 19 Mar 2020 00:00:00 +0000</pubDate><guid>https://hyan46.github.io/project/ai-manufacturing/</guid><description>&lt;h2 id="overall-information">Overall Information&lt;/h2>
&lt;p>This project uses artificial intelligence and machine learning methods to develop algorithms for anomaly detection and quality prediciton in the manufacturing systems considering the heterogeneous data types in manufacturing systems (e.g., images, signals).&lt;/p></description></item></channel></rss>