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黃文賢
主任工程師 @ 群創光電股份有限公司 InnoLux Corporation
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黃文賢

主任工程師 @ 群創光電股份有限公司 InnoLux Corporation
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群創光電股份有限公司 InnoLux Corporation
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國立中央大學 National Central University
臺南市, 台灣
Taiwan

Featured Resume

Uploaded on Dec 23rd 2025

Professional Background

  • Current Status
    Employed
  • Profession
    Data Scientist
    Machine Learning Engineer
  • Fields
    Artificial Intelligence / Machine Learning
    Big Data
  • Work Experience
    More than 15 years (More than 15 years relevant)
  • Management
  • Skills
    Agentic AI
    Knowledge Graph
    Conversational UI
    Neuro-symbolic AI
    Causal Inference
  • Highest Level of Education

Job Search Preferences

  • Current Status
    Open to opportunities
  • Desired Job Type
  • Desired Positions
  • Desired Work Locations
  • Freelance

Work Experience

Education

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Doctor of Philosophy (PhD)
Computer Science and Information Engineering
2025 - 2029
Description
PhD Researcher / Graduate Research Assistant, National Central University, Taiwan Sep 2025 - Present Gen AI / Multi-Agent Systems / Knowledge Graph / Neuro-Symbolic AI/Causal Inference/NLP ● Enterprise Knowledge Graph (KG): Developed a high-precision KG for manufacturing control plans and design parameters, enabling cross-document retrieval and zero-hallucination querying for industrial standards. ● Predictive Diagnostics: Integrated Bayesian Networks with KG and LLMs to infer potential impacts on yield and reliability by reasoning through historical event correlations. ● Intelligent KM Copilot: Engineered a personalized Knowledge Management system with long-term memory and automated SWOT analysis, proactively guiding users with "Golden Rules" based on behavior patterns. ● Neuro-Symbolic Reasoning: Built a logic-based framework to verify design rule compliance; combined qualitative historical insights from KG to assess risks in real-time manufacturing events. ● Conversational AI & Auto-Scripting: Implemented a Text-to-Script engine that automatically generates and confi gures testing scripts based on natural language user requirements. ● Multi-Agent Hierarchy: Designed a Multi-Agent system using hierarchical planning to decompose complex queries into sub-tasks, featuring autonomous tool-use and self-correction for unexpected edge cases.