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Ming-Kai Liu
Junior AI Engineer specializing in LLM pipelines, RAG, and computer vision
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About
Built and deployed an on-prem, HIPAA-compliant LLM pipeline for oncology-focused clinical note generation and decision support, emphasizing grounded differential diagnosis and explainable reasoning via RAG to reduce hallucinations. Also created a LangGraph-based multi-agent academic paper search system integrating Tavily, arXiv, and Semantic Scholar with an orchestrator that routes tasks to specialized sub-agents.
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Key Strengths
- Built and deployed a HIPAA-compliant, on-prem LLM clinical documentation/decision-support pipeline
- Strong hallucination-mitigation approach using RAG and grounding outputs in internal data/conversations
- Designs LLMs as constrained extractors/rule-checkers rather than free-form generators for safety-critical domains
- Experience orchestrating multi-agent workflows with LangGraph (search, retrieval, summarization agents)
- Metrics-driven agent/workflow design with scenario/edge-case testing and detailed action logging for debugging
- Pragmatic model/retrieval/prompt selection based on task complexity, latency, and query type
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