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wangxb96/README.md

👋 Hi there! I'm Wangxb

Google Scholar GitHub

I'm a researcher passionate about advancing AI, with a focus on machine learning, data mining, and optimization.

🚀 About Me

  • 🎓 AI Researcher
  • 🔬 Interests: Machine Learning, Feature Selection, Evolutionary Algorithms, LLMs
  • 💻 Tech Stack: Python, MATLAB, C++, PyTorch, Pandas, NumPy, Scikit-learn
  • 📊 GitHub Stats:

🔥 Featured Projects

🧠 Research Focus

  • Feature Selection & Engineering
  • Evolutionary Algorithms & Optimization
  • ML for Bioinformatics
  • Cancer Biomarker Identification
  • Nature-inspired Computation
  • Large Language Models

📚 Publications

Published in top journals including:

  • IEEE/ACM TCBB
  • IEEE TKDE
  • Expert Systems With Applications
  • Knowledge-Based Systems

🤝 Connect with Me

Feel free to reach out for research discussions or collaboration ideas!

Pinned Loading

  1. SaWDE SaWDE Public

    Code of the paper:A Self-adaptive Weighted Differential Evolution Approach for Large-scale Feature Selection --[Knowledge-Based Systems 22]

    MATLAB 32 5

  2. EODE EODE Public

    Code for: Exhaustive Exploitation of Nature-inspired Computation for Cancer Screening in an Ensemble Manner -- [IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB 24)]

    MATLAB 2 1

  3. MEL MEL Public

    Code for “MEL: Efficient Multi-Task Evolutionary Learning for High-Dimensional Feature Selection“--[IEEE Transactions on Knowledge and Data Engineering (TKDE 24)]

    MATLAB 9 3

  4. Awesome-EdgeAI Awesome-EdgeAI Public

    Resources of our survey paper "A Comprehensive Survey on AI Integration at the Edge: Techniques, Applications, and Challenges"

    54 6

  5. HSNOE HSNOE Public

    Code for “Evolving Pathway Activation from Cancer Gene Expression Data using Nature-inspired Ensemble Optimization”--[Expert Systems With Applications 24]

    MATLAB 1

  6. RAG-QA-Generator RAG-QA-Generator Public

    RAG-QA-Generator 是一个用于检索增强生成(RAG)系统的自动化知识库构建与管理工具。该工具通过读取文档数据,利用大规模语言模型生成高质量的问答对(QA对),并将这些数据插入数据库中,实现RAG系统知识库的自动化构建和管理。

    Python 53 5