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Matrix Lab - Leading research laboratory specializing in blockchain technology, federated learning, smart contracts, Web 3.0 ecosystems, IoT applications, and edge computing. Discover our latest publications and innovations.

Matrix Lab - Blockchain & Federated Learning Research

Welcome to Matrix Lab! We are a cutting-edge research laboratory focused on advancing blockchain technology, federated learning, intelligent edge computing, and Web 3.0 ecosystems. Our mission is to drive innovation in decentralized systems, smart contract security, and cross-chain interoperability.

🔬 Research Excellence

Matrix Lab is at the forefront of academic research with publications in top-tier journals and conferences including:

  • IEEE Transactions on Information Forensics and Security
  • IEEE Internet of Things Journal
  • IEEE INFOCOM
  • IEEE ICDE
  • Neural Networks
  • Science China Information Sciences

📰 Latest News & Publications (2025)

Recent Achievements:

  • ✅ IEEE Transactions on Information Forensics and Security - “Connector: Enhancing the traceability of decentralized bridge applications via automatic cross-chain transaction association” ACCEPTED
  • ✅ IEEE Internet of Things Journal - “MMFed: A Multimodal Federated Learning Framework for Heterogeneous Devices” ACCEPTED
  • ✅ IEEE Global Blockchain Conference (GBC) - “Q-DPoS: An Improved DPoS Consensus based on Quadratic Voting Mechanism in Web 3.0” ACCEPTED
  • ✅ IEEE Global Blockchain Conference (GBC) - “A Semantic Detection Incentive Mechanism For Blockchain Transactions Based on Evolutionary Game Theory in Web3 Ecosystem” ACCEPTED
  • ✅ Neural Networks - “Enhancing partition distinction: A contrastive policy to recommendation unlearning” ACCEPTED
  • ✅ IEEE Internet of Things Journal - “Exploring AIoT Blockchain Transaction Semantic Detection and Incentive Mechanism with Evolutionary Game Towards Web 3.0 Ecosystem” ACCEPTED
  • ✅ Science China Information Sciences - “Agent4Vul: multimodal LLM agents for smart contract vulnerability detection” ACCEPTED
  • ✅ IEEE INFOCOM 2025 - “ContribChain: A Stress-Balanced Blockchain Sharding Protocol with Node Contribution Awareness” ACCEPTED
  • ✅ IEEE ICDE 2025 - “Know Your Account: Double Graph Inference-Based Account De-Anonymization on Ethereum” ACCEPTED
  • 📄 arXiv preprint - “CodeBC: A More Secure Large Language Model for Smart Contract Code Generation in Blockchain” PUBLISHED

🎯 Core Research Areas

Blockchain Technology

Advanced research in consensus mechanisms, cross-chain transactions, smart contract security, and decentralized applications (DApps). We focus on improving blockchain scalability, security, and interoperability.

Key Topics:

  • Consensus Algorithms (DPoS, PoS, BFT)
  • Cross-chain Bridge Security
  • Smart Contract Vulnerability Detection
  • Blockchain Sharding Protocols
  • Account De-anonymization

Federated Learning

Pioneering multimodal federated learning frameworks for heterogeneous devices and cross-domain IoT applications. Our research enables privacy-preserving machine learning across distributed systems.

Key Topics:

  • Multimodal Federated Learning
  • Privacy-Preserving ML
  • Heterogeneous Device Collaboration
  • Edge-Cloud Federated Systems

Web 3.0 Ecosystem

Building the next generation of decentralized web infrastructure with focus on incentive mechanisms, semantic detection, and evolutionary game theory applications.

Key Topics:

  • Decentralized Applications (DApps)
  • Token Economics & Incentive Design
  • Web3 Security & Privacy
  • Semantic Transaction Analysis

Intelligent Edge Computing & IoT

Developing edge intelligence solutions for AIoT applications, enabling real-time processing and decision-making at the network edge.

Key Topics:

  • Edge Intelligence
  • AIoT Applications
  • Distributed Computing
  • Real-time Data Processing

AI & Machine Learning

Applying artificial intelligence and large language models to blockchain security, smart contract analysis, and recommendation systems.

Key Topics:

  • LLM for Smart Contract Security
  • Recommendation Unlearning
  • AI-driven Vulnerability Detection
  • Multimodal AI Systems

🔗 Quick Navigation

🏢 Matrix Lab Ecosystem

Ke Entropy Technology (刻熵科技)

Our commercial arm translating research into practical blockchain security solutions and Web3 products.

Visit Ke Entropy →

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🤝 Collaboration & Contact

We welcome collaboration opportunities with researchers, institutions, and industry partners. For research inquiries, partnership proposals, or academic collaboration, please reach out through our GitHub repository.

Keywords: Blockchain, Federated Learning, Web 3.0, Smart Contracts, IoT, Edge Computing, Consensus Mechanisms, Cross-chain, DeFi, DApps, AI Security, Machine Learning, Decentralized Systems, 区块链, 联邦学习, 智能合约, 物联网