<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>AI for Science | Peilong Ma</title><link>https://mplebron.github.io/tags/ai-for-science/</link><atom:link href="https://mplebron.github.io/tags/ai-for-science/index.xml" rel="self" type="application/rss+xml"/><description>AI for Science</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Tue, 10 Mar 2026 00:00:00 +0000</lastBuildDate><image><url>https://mplebron.github.io/media/icon_hu68170e94a17a2a43d6dcb45cf0e8e589_3079_512x512_fill_lanczos_center_3.png</url><title>AI for Science</title><link>https://mplebron.github.io/tags/ai-for-science/</link></image><item><title>Optimizing AI-driven Geographic Simulation Task Scheduling through Intelligent Runtime Estimation for Distributed Heterogeneous Clusters</title><link>https://mplebron.github.io/publication/ai-geo-simulation-scheduling-under-review/</link><pubDate>Tue, 10 Mar 2026 00:00:00 +0000</pubDate><guid>https://mplebron.github.io/publication/ai-geo-simulation-scheduling-under-review/</guid><description>&lt;p>This under-review work studies how runtime estimation and resource-aware scheduling can improve throughput and balance for AI-driven geo-simulation tasks on distributed heterogeneous clusters.&lt;/p></description></item></channel></rss>