<?xml version="1.0" encoding="utf-8" standalone="yes" ?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>Yangfan Jiang | Trustworthy Engineering of Software Technologies (TEST) Lab</title>
    <link>https://nus-test.github.io/author/yangfan-jiang/</link>
      <atom:link href="https://nus-test.github.io/author/yangfan-jiang/index.xml" rel="self" type="application/rss+xml" />
    <description>Yangfan Jiang</description>
    <generator>Wowchemy (https://wowchemy.com)</generator><language>en-us</language><lastBuildDate>Wed, 21 Oct 2026 15:00:00 +0000</lastBuildDate>
    <image>
      <url>https://nus-test.github.io/media/logo_hu54a81beaedce3437486bda7d4bb96888_11488_300x300_fit_lanczos_3.png</url>
      <title>Yangfan Jiang</title>
      <link>https://nus-test.github.io/author/yangfan-jiang/</link>
    </image>
    
    <item>
      <title>Learning With Fine-Grained Privacy</title>
      <link>https://nus-test.github.io/event/261021/</link>
      <pubDate>Wed, 21 Oct 2026 15:00:00 +0000</pubDate>
      <guid>https://nus-test.github.io/event/261021/</guid>
      <description>&lt;p&gt;Speaker Info:&lt;/p&gt;
&lt;p&gt;&lt;a href=&#34;https://yangfan-jiang.github.io/&#34; target=&#34;_blank&#34; rel=&#34;noopener&#34;&gt;Yangfan Jiang&lt;/a&gt; is a Ph.D. candidate in Computer Science at the National University of Singapore, advised by &lt;a href=&#34;https://www.comp.nus.edu.sg/~xiaoxk/&#34; target=&#34;_blank&#34; rel=&#34;noopener&#34;&gt;Prof. Xiaokui Xiao&lt;/a&gt;. His research focuses on privacy and security for modern AI over sensitive data, including algorithms that enable large language models and data analytics methods to learn from private data with formal privacy and security guarantees.&lt;/p&gt;
</description>
    </item>
    
  </channel>
</rss>
