<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:atom="http://www.w3.org/2005/Atom" version="2.0">
  <channel>
    <docs>http://www.rssboard.org/rss-specification</docs>
    <atom:link rel="self" type="application/rss+xml" href="https://escholarship.org/uc/ucrlibrary_aigrbgs/rss"/>
    <ttl>720</ttl>
    <title>Recent ucrlibrary_aigrbgs items</title>
    <link>https://escholarship.org/uc/ucrlibrary_aigrbgs/rss</link>
    <description>Recent eScholarship items from UCR AI Graduate Research Brown Bag Series</description>
    <pubDate>Thu, 10 Sep 2026 17:31:03 +0000</pubDate>
    <item>
      <title>NuclearGuard AI Agent-Assisted Radiation Anomaly Detection and Operator Decision Support Using Gamma-Ray Spectral Data</title>
      <link>https://escholarship.org/uc/item/0c67f27h</link>
      <description>This presentation introduces NuclearGuard AI, an interactive nuclear safety dashboard that applies deep learning and anomaly detection to public gamma-ray spectral data. The prototype visualizes radiation spectra, anomaly scores, reconstruction errors, and spatial risk patterns to help identify suspicious radiological signals. Using Streamlit, Plotly, and machine learning models such as Isolation Forest and deep autoencoders, the project demonstrates how AI can support radiation monitoring, interpretable nuclear safety analysis, and operator decision-making.</description>
      <guid isPermaLink="true">https://escholarship.org/uc/item/0c67f27h</guid>
      <pubDate>Tue, 2 Jun 2026 00:00:00 +0000</pubDate>
      <author>
        <name>Fang, Yung-Sian</name>
      </author>
    </item>
    <item>
      <title>Inaugural UCR AI Graduate Research Brown Bag Series Event Flyer</title>
      <link>https://escholarship.org/uc/item/4bp8n5kj</link>
      <description>Inaugural UCR AI Graduate Research Brown Bag Series Event Flyer</description>
      <guid isPermaLink="true">https://escholarship.org/uc/item/4bp8n5kj</guid>
      <pubDate>Tue, 26 May 2026 00:00:00 +0000</pubDate>
      <author>
        <name>Shin, Inyoung</name>
      </author>
    </item>
  </channel>
</rss>
