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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.1//EN"
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<meta name="description" content="SAIL Lab — Safe AI and Robot Learning Lab at Shanghai Jiao Tong University. Reinforcement learning, AI safety, robot learning, and foundation-model agents, led by Prof. Shangding Gu." />
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<title>SAIL Lab | Safe AI and Robot Learning Lab @ SJTU</title>
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<a href="index.html">SAIL Lab</a>
<span class="brand-sub">Safe AI and Robot Learning Lab · Shanghai Jiao Tong University</span>
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<a href="https://github.com/SAIL-Research-Lab" target="_blank" title="SAIL Lab GitHub"><svg viewBox="0 0 16 16" aria-hidden="true"><path fill-rule="evenodd" d="M8 0C3.58 0 0 3.58 0 8c0 3.54 2.29 6.53 5.47 7.59.4.07.55-.17.55-.38 0-.19-.01-.82-.01-1.49-2.01.37-2.53-.49-2.69-.94-.09-.23-.48-.94-.82-1.13-.28-.15-.68-.52-.01-.53.63-.01 1.08.58 1.23.82.72 1.21 1.87.87 2.33.66.07-.52.28-.87.51-1.07-1.78-.2-3.64-.89-3.64-3.95 0-.87.31-1.59.82-2.15-.08-.2-.36-1.02.08-2.12 0 0 .67-.21 2.2.82.64-.18 1.32-.27 2-.27.68 0 1.36.09 2 .27 1.53-1.04 2.2-.82 2.2-.82.44 1.1.16 1.92.08 2.12.51.56.82 1.27.82 2.15 0 3.07-1.87 3.75-3.65 3.95.29.25.54.73.54 1.48 0 1.07-.01 1.93-.01 2.2 0 .21.15.46.55.38A8.01 8.01 0 0 0 16 8c0-4.42-3.58-8-8-8z"/></svg></a>
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<!-- =========================== Welcome =========================== -->
<div class="welcome">
<h1>Welcome to SAIL Lab</h1>
<div class="tagline">Safe AI and Robot Learning Lab — School of Computer Science, Shanghai Jiao Tong University</div>
<p style="font-size: 18px; text-align: justify;">
We are a research group working on <b>reinforcement learning, planning, and AI safety</b>, with applications in
foundation models (e.g., large language models and multimodal models), robotics, and autonomous systems.
Our goal is to design <b>safe, reliable, and efficient learning systems</b> that address pressing real-world
challenges — from trustworthy decision-making for embodied agents to scalable and dependable AI.
The lab is led by <a href="group.html">Prof. Shangding Gu (顾尚定)</a>.
</p>
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<p style="margin-bottom: 6px; text-align: left;">
<b>We are looking for highly self-motivated undergraduate students, graduate (MS/PhD) students, and visiting/intern students</b>
who are passionate about <span class="venue">reinforcement learning, AI safety, machine learning, large language models, and robotics</span>.
If you are interested in our research, please contact us with details about your background and relevant skills.
</p>
<a class="btn navy" href="join.html">Join SAIL Lab →</a>
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<!-- =========================== Sponsors =========================== -->
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<p>
We gratefully acknowledge the support of the following organizations, which enable our research on safe and reliable AI:
</p>
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<img src="images/sponsors/openai.svg" alt="OpenAI" />
<span class="s-name">OpenAI</span>
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<img src="images/sponsors/nvidia.svg" alt="NVIDIA" />
<span class="s-name">NVIDIA</span>
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<span class="s-name">TITAN Group (Greece)</span>
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<span class="s-textlogo"><span class="nsfc">NSFC</span></span>
<span class="s-name">国家自然科学基金委员会<br/>(National Natural Science Foundation of China)</span>
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<img src="images/SJTU-logo.svg" alt="Shanghai Jiao Tong University" />
<span class="s-name">Shanghai Jiao Tong University</span>
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<b>Agentic AI Frontier Seminar</b> — an online seminar series on frontier research in agentic AI.
Visit the seminar homepage for the speaker lineup, schedule, and past talks.
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<a class="btn navy" href="https://agentic-ai-frontier-seminar.github.io/" target="_blank">Seminar Homepage →</a>
</div>
<!-- =========================== News =========================== -->
<h2>Recent News</h2>
<ul style="list-style: none; padding-left: 0;">
<li class="news-item">07.2026: Gave a talk on Agentic AI for Semiconductor Manufacturing at <a href="https://www.lamresearch.com/" target="_blank">Lam Research</a>.</li>
<li class="news-item">07.2026: Gave a talk on Agentic AI Scaling at <a href="https://xhslink.cn/o/1aZLjyRO674" target="_blank">Shanghai AI Lab</a>.</li>
<li class="news-item">03.2026: Our papers on reinforcement learning for drug design got accepted by <span class="venue">Science Advances</span>.</li>
<li class="news-item">03.2026: Invited to serve as an Area Chair for <a href="https://neurips.cc/Conferences/2026" target="_blank">NeurIPS 2026</a>.</li>
<li class="news-item">11.2025: Gave a talk on Safe Robot Learning at <a href="https://sites.google.com/berkeley.edu/lemas-seminar" target="_blank">Shankar Sastry Group</a>, UC Berkeley.</li>
<li class="news-item">10.2025: Gave a talk on Safe Learning at the Applied Mathematics and Statistics Department Postdoctoral Seminar at Johns Hopkins University.</li>
<li class="news-item">09.2025: Our papers on safe RL and LLMs got accepted by <span class="venue">NeurIPS 2025</span> and <span class="venue">EMNLP 2025</span>.</li>
<li class="news-item">08.2025: Talk at the <a href="https://meetings.informs.org/wordpress/annual/" target="_blank">2025 INFORMS Annual Meeting</a>, Atlanta, Georgia, USA (October 26–29).</li>
<li class="news-item">07.2025: We released <strong>Agentic Web</strong>, a study on web agent research: <a href="https://arxiv.org/pdf/2507.21206?" target="_blank">Paper</a> | <a href="https://github.com/SafeRL-Lab/agentic-web" target="_blank">Github</a>.</li>
<li class="news-item">05.2025: We released <strong><a href="https://open-space-reasoning.github.io" target="_blank">M4R</a></strong>, a benchmark for massive multimodal understanding and reasoning in open space (code, dataset and leaderboard available at <a href="https://open-space-reasoning.github.io" target="_blank">open-space-reasoning.github.io</a>).</li>
<li class="news-item">05.2025: We released <strong><a href="https://github.com/SafeRL-Lab/BenchNetRL" target="_blank">RLBenchNet</a></strong>, a systematic benchmarking suite for evaluating neural network architectures in reinforcement learning.</li>
<li class="news-item">04.2025: Gave a talk on Safe Robot Learning at <a href="https://msl.stanford.edu/" target="_blank">Mac Schwager's Lab</a>, Stanford University.</li>
<li class="news-item">03.2025: <span class="venue">Received a grant</span> from <a href="https://www.nvidia.com/en-us/" target="_blank">Nvidia</a> to support our research!</li>
<li class="news-item">03.2025: Lead guest editor for the Special Issue on <em>Trustworthy AI for Automation Control of Embodied Agents in the Era of Foundation Models</em> in <a href="https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=8856" target="_blank">IEEE Transactions on Automation Science and Engineering</a> (<a href="./papers/IEE_TASE_Special_Issue_EAI_CFP.pdf" target="_blank">Call for Papers</a>).</li>
<li class="news-item">01.2025: Our paper on robust reinforcement learning got accepted by <span class="venue">ICLR 2025</span>.</li>
<li class="news-item">01.2025: We launched the 1st International Workshop on AI Agent Reasoning and Decision-Making (AIR 2025) — <a href="https://ai-agent-reasoning.com/" target="_blank">workshop homepage</a>.</li>
<li class="news-item">01.2025: <span class="venue">Received a grant</span> from <a href="https://openai.com/" target="_blank">OpenAI</a> to support our research!</li>
<li class="news-item">01.2025: Our paper on safe multi-objective reinforcement learning got accepted by <span class="venue">IEEE Transactions on Pattern Analysis and Machine Intelligence</span>.</li>
</ul>
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© 2026 SAIL Lab (Safe AI and Robot Learning Lab) — School of Computer Science, Shanghai Jiao Tong University<br/>
Principal Investigator: Prof. Shangding Gu (顾尚定) ·
<a href="mailto:shangding.gu@sjtu.edu.cn">shangding.gu@sjtu.edu.cn</a> ·
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