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Lance Chou
Intern Machine Learning Engineer specializing in NLP and MLOps
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About
PhD-led research engineer who has shipped LLM-powered agents for automated knowledge extraction from STEM textbooks/papers into a graph database, reporting a 90% accuracy improvement and major reductions in manual curation time. Also built an end-to-end multi-agent news aggregation/sentiment pipeline using the Agno framework with Pydantic-structured outputs, retries, and monitoring, and has experience processing messy SEC filings.
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Key Strengths
- Built LLM pipeline to extract/deduplicate STEM knowledge into a graph database
- Improved extraction accuracy by 90% via ML-guided extraction and retrieval
- Designed reliability mechanisms for math-heavy pipelines (equation checks, DB verifications, automated logging)
- Architected multi-agent workflow (4 agents) with structured Pydantic state and orchestration via Agno
- Implemented real-world robustness with prompt tuning, malformed-output handling, retries, and default outputs
- Experience handling messy SEC filings with inconsistent formats (tables/math-heavy) using pattern-based normalization and deduplication
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