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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Renjun Xu - AI Research Portfolio</title>
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}
}
</style>
</head>
<body>
<div class="container">
<header>
<div class="profile-section">
<div class="profile-img">🧠</div>
<div>
<h1>Dr. Renjun XU</h1>
<div class="tagline">Reliable Foundation Models & Scientific AI</div>
<div class="subtitle" style="font-size: 1rem; opacity: 0.85; margin-top: 0.5rem;">
Zhejiang University, ZJU100 Young Professor & Deputy Director | Former Senior Director, Global Data & AI (VISA)
</div>
<div class="contact-info">
<div class="contact-item">
<a href="mailto:xu at tensense.org" class="social-link">
<span>📧</span>
<span>Contact: xu at tensense dot org</span>
</a>
</div>
<div class="social-link">
<span>🏛️</span>
<span>Zhejiang University</span>
</div>
<div class="contact-item">
<a href="https://github.com/scienceaix/deepresearch" class="social-link">
<span>💻</span>
<span>GitHub</span>
</a>
</div>
</div>
</div>
</header>
<nav>
<ul>
<li><a href="#overview">Overview</a></li>
<li><a href="#research">Research Areas</a></li>
<li><a href="#publications">Key Publications</a></li>
<li><a href="#projects">Open Source</a></li>
<li><a href="#technical">Technical Stack</a></li>
<li><a href="#contact">Connect</a></li>
</ul>
</nav>
<main>
<section id="overview" class="section">
<h2>🎯 Research Leadership Profile</h2>
<div class="highlight-box">
<p>An AI research scientist and physicist with 15+ years experience bridging cutting-edge machine learning research and large-scale applications, making our models be more reliable and OOD generalizable. Former <strong>Senior Director of Global Data and AI at VISA</strong> leading global AI initiatives serving 3B+ users, and currently <strong>ZJU100 Young Professor & Deputy Director at Zhejiang University</strong> in China. Led international research teams, published 30+ papers in top venues (CVPR, NeurIPS, IJCAI, Nature Communications), and secured $1.2M+ in competitive research funding. Research adopted by major AI labs and cited by multiple IEEE fellows with work reaching multiple ESI highly cited status.</p>
</div>
<div class="stats-grid">
<div class="stat-card">
<div class="stat-number">30+</div>
<div>Top-Tier Publications</div>
</div>
<div class="stat-card">
<div class="stat-number">2</div>
<div>ESI Highly Cited Papers in 2025</div>
</div>
<div class="stat-card">
<div class="stat-number">3B</div>
<div>Users Impacted at VISA</div>
</div>
<div class="stat-card">
<div class="stat-number">1B-100B</div>
<div>Multi-Scale Large Foundation Model Development</div>
</div>
</div>
</section>
<section id="research" class="section">
<h2>🔬 Research Areas</h2>
<h3>Foundation Models & Advanced ML</h3>
<div class="highlight-box">
<p><strong>Large Language Models:</strong> Co-developed from 1B to 100B parameter foundation models with novel reasoning architectures. Research on mathematical reasoning, rule-based computation, and reliability in LLM outputs.</p>
<p><strong>Model Generalization:</strong> Revolutionary optimal transport-based domain adaptation methods (CVPR 2020, 200+ citations). Solved critical transfer learning challenges enabling models to generalize across domains.</p>
<p><strong>Multimodal AI:</strong> Novel MetaRuleReasoner framework and multimodal logical reasoning chains across text, image, and structured data.</p>
</div>
<h3>AI for Scientific Discovery</h3>
<div class="highlight-box">
<p><strong>Materials Science:</strong> S2SNet - First AI achieving 92% accuracy in superconductor discovery. Published in IJCAI 2022 and NeurIPS 2022.</p>
<p><strong>Chemistry & Biology:</strong> Comprehensive survey of scientific LLMs (ACM Computing Surveys, IF: 23.8). Retrosynthesis prediction using iterative string editing (Nature Communications).</p>
<p><strong>Physics-Informed Neural Networks:</strong> E(2)-equivariant vision transformers leveraging group theory. Spatial coherence instructed swin transformer applied for universal holographic imaging.</p>
</div>
<h3>Production ML Systems</h3>
<div class="highlight-box">
<p><strong>Recommendation Systems:</strong> Novel time-series recommendation addressing dynamic missing data (MNAR) challenges. Published in IEEE TKDE (CCF-A, IF: 11.6).</p>
<p><strong>Enterprise Applications:</strong> Full lifecycle user behavior modeling for e-commerce (KDD 2023, CCF-A). Scalable systems serving millions of users.</p>
</div>
</section>
<section id="publications" class="section">
<h2>📚 Key Publications</h2>
<div class="research-item">
<div class="research-title">Reliable Weighted Optimal Transport for Unsupervised Domain Adaptation</div>
<div class="research-venue">CVPR 2020 (CCF-A) | 200+ Citations | World AI Conference Outstanding Youth Paper Award</div>
<div class="research-desc">Revolutionary method solving model transfer challenges using optimal transport theory. Collaboration with Stanford University and Microsoft Research. </div>
</div>
<div class="research-item">
<div class="research-title">Joint Partial Optimal Transport for Open Set Domain Adaptation</div>
<div class="research-venue">IJCAI 2020 (CCF-A) | 50+ Citations </div>
<div class="research-desc">The first optimal transport method for open set domain adaptation. Collaboration with Stanford University and Microsoft Research. </div>
</div>
<div class="research-item">
<div class="research-title">Personalized Federated Learning with Adaptive Batchnorm for Healthcare</div>
<div class="research-venue">IEEE Transactions on Big Data | ESI Highly Cited </div>
<div class="research-desc">A personalized federated learning method that handles non-IID healthcare data. Collaboration with Microsoft Research. </div>
</div>
<div class="research-item">
<div class="research-title">S2SNet: A Pretrained Neural Network for Superconductivity Discovery</div>
<div class="research-venue">IJCAI 2022 (CCF-A)</div>
<div class="research-desc">First AI model achieving 92% accuracy in superconductor prediction. Breakthrough application of deep learning to materials discovery.</div>
</div>
<div class="research-item">
<div class="research-title">Retrosynthesis Prediction with an Iterative String Editing Model</div>
<div class="research-venue">Nature Communications 2024 (IF: 15.7)</div>
<div class="research-desc">Novel approach to chemical synthesis planning using iterative string editing. Interdisciplinary collaboration advancing computational chemistry.</div>
</div>
<div class="research-item">
<div class="research-title">Scientific Large Language Models: A Survey on Biological & Chemical Domains</div>
<div class="research-venue">ACM Computing Surveys 2025 (IF: 23.8)</div>
<div class="research-desc">Comprehensive survey of AI for scientific discovery, covering foundation models in biology, chemistry, and materials science.</div>
</div>
<div class="research-item">
<div class="research-title">Do Large Language Models Truly Grasp Addition? A Rule-Focused Diagnostic Using Two-Integer Arithmetic</div>
<div class="research-venue">EMNLP 2025</div>
<div class="research-desc">Revealing current LLMs though succeed in numeric accuracy yet fail core arithmetic computation (like commutativity, symbolic invariance, and scaling). Collaboration with Westlake University.</div>
</div>
<div class="research-item">
<div class="research-title">MetaRuleReasoner: Beyond Chain-of-Thought Reasoning</div>
<div class="research-venue">Submitted to ICLR 2026</div>
<div class="research-desc">Neural rule-based reasoning framework achieving 100% accuracy for reliable mathematical computation. Addresses fundamental limitations in LLM reasoning.</div>
</div>
<div class="highlight-box">
<p><strong>Full Publication List:</strong> 30+ papers in CVPR, NeurIPS, IJCAI, KDD, EMNLP, ACL, UAI, Nature Communications, ACM Computing Surveys, IEEE TKDE, and other premier venues. Multiple work reaching ESI highly cited status.</p>
</div>
</section>
<section id="projects" class="section">
<h2>💻 Open Source & Code Repositories</h2>
<div class="repo-card">
<div class="repo-header">
<a href="https://github.com/scienceaix/deepresearch">
<span class="repo-name">🌟 deepresearch</span>
</a>
</div>
<p style="color: #8b949e;">Comprehensive survey of deep research systems, methodologies, and applications. Followed by researchers at Google DeepMind, leading universities, and major tech companies.</p>
<div class="repo-stats">
<span>⭐ 400+ stars</span>
<span>🔄 Actively maintained</span>
<span>📖 arXiv:2506.12594</span>
</div>
</div>
<div class="repo-card">
<div class="repo-header">
<a href="https://github.com/supercond/S2SNet">
<span class="repo-name">s2snet-superconductor</span>
</a>
</div>
<p style="color: #8b949e;">Pre-trained neural network for superconductivity discovery achieving 92% accuracy. IJCAI 2022 research implementation.</p>
<div class="repo-stats">
<span>📄 IJCAI 2022</span>
<span>⚛️ Materials Science</span>
<span>🎯 92% Accuracy</span>
</div>
</div>
<div class="repo-card">
<div class="repo-header">
<a href="https://github.com/scienceaix/MetaRuleReasoner">
<span class="repo-name">metarule-reasoner</span>
</a>
</div>
<p style="color: #8b949e;">Neural rule-based reasoning for reliable mathematical computation. Beyond chain-of-thought approaches with 100% accuracy guarantee.</p>
<div class="repo-stats">
<span>🧮 Math Reasoning</span>
<span>✅ 100% Accuracy</span>
<span>🔬 Under Review</span>
</div>
</div>
</section>
<section id="technical" class="section">
<h2>🛠️ Technical Expertise</h2>
<div class="tech-grid">
<div class="tech-category">
<h4>Foundation Models</h4>
<div class="tech-tag">Transformers</div>
<div class="tech-tag">LLMs</div>
<div class="tech-tag">Multimodal AI</div>
<div class="tech-tag">RLHF</div>
<div class="tech-tag">RL Agents</div>
<div class="tech-tag">RAG</div>
<div class="tech-tag">Prompt Engineering</div>
<div class="tech-tag">Knowledge Distillation</div>
</div>
<div class="tech-category">
<h4>Advanced ML</h4>
<div class="tech-tag">Optimal Transport</div>
<div class="tech-tag">Domain Adaptation</div>
<div class="tech-tag">Few-Shot Learning</div>
<div class="tech-tag">Meta-Learning</div>
<div class="tech-tag">Graph Neural Networks</div>
<div class="tech-tag">Knowledge Graph</div>
<div class="tech-tag">Self-Supervised</div>
</div>
<div class="tech-category">
<h4>Scientific Computing</h4>
<div class="tech-tag">Physics-Informed NNs</div>
<div class="tech-tag">Molecular Modeling</div>
<div class="tech-tag">Materials Discovery</div>
<div class="tech-tag">Equation Learning</div>
<div class="tech-tag">Symbolic Regression</div>
<div class="tech-tag">Scientific Workflows</div>
</div>
<div class="tech-category">
<h4>Infrastructure</h4>
<div class="tech-tag">PyTorch</div>
<div class="tech-tag">TensorFlow</div>
<div class="tech-tag">Distributed Training</div>
<div class="tech-tag">CUDA/GPU</div>
<div class="tech-tag">MLOps</div>
<div class="tech-tag">Cloud Platforms</div>
</div>
</div>
</section>
<section id="contact" class="section">
<h2>🤝 Research Collaborations</h2>
<div class="highlight-box">
<p>Open to collaborative research advancing foundation models, scientific AI, and systems bridging theoretical innovation with real-world impact. Interested in partnerships with research organizations, universities, and companies working on frontier AI challenges.</p>
<div style="margin-top: 1.5rem; color: #c9d1d9;">
<p><strong>Research Interests:</strong></p>
<p>• Foundation model architectures and efficient training</p>
<p>• AI for autonomous scientific discovery</p>
<p>• Model generalization and transfer learning</p>
<p>• Production ML systems at scale</p>
<p>• Academic-industry research partnerships</p>
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<p><strong>Get in touch:</strong> Contact via Email or GitHub for research discussions and partnership opportunities.</p>
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<strong>📧 Email:</strong> xu at tensense dot org<br>
<strong>🏛️ Institution:</strong> Zhejiang University<br>
<strong>🐙 GitHub:</strong> https://github.com/scienceaix/deepresearch<br>
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<p>© 2025 Renjun Xu | Advancing Foundation Models & Scientific AI</p>
<p>Building bridges between cutting-edge research and transformative applications</p>
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