<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Shuyang Li | HEAD Lab</title><link>https://verimaketest.github.io/author/shuyang-li/</link><atom:link href="https://verimaketest.github.io/author/shuyang-li/index.xml" rel="self" type="application/rss+xml"/><description>Shuyang Li</description><generator>Wowchemy (https://wowchemy.com)</generator><language>en-us</language><lastBuildDate>Wed, 01 Apr 2026 00:00:00 +0000</lastBuildDate><image><url>https://verimaketest.github.io/media/icon_hu0ab5c02c1f2ff27bbe76bf3235245d1a_922260_512x512_fill_lanczos_center_3.png</url><title>Shuyang Li</title><link>https://verimaketest.github.io/author/shuyang-li/</link></image><item><title>TrackGNN: A Highly Parallelized and Self-Adaptive GNN Accelerator for Track Reconstruction on FPGAs</title><link>https://verimaketest.github.io/publication/li-2026-trackgnn/</link><pubDate>Wed, 01 Apr 2026 00:00:00 +0000</pubDate><guid>https://verimaketest.github.io/publication/li-2026-trackgnn/</guid><description/></item><item><title>FPGA-Based Sparse Matrix Multiplication Accelerators: From State-of-the-Art to Future Opportunities</title><link>https://verimaketest.github.io/publication/liu-2024-fpga/</link><pubDate>Fri, 01 Nov 2024 00:00:00 +0000</pubDate><guid>https://verimaketest.github.io/publication/liu-2024-fpga/</guid><description/></item></channel></rss>