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Riya Stanly
Intern Data Scientist specializing in machine learning, NLP, and LLM fine-tuning
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About
Built a production-style AI meeting summarization and action-item extraction system (Azure Speech-to-Text + transformer summarization/NER) exposed via a Flask REST API, with explicit guardrails to prevent hallucinated tasks. Strong focus on reliability: modular agent/workflow design, precision-first evaluation with human-validated golden notes, and practical orchestration patterns (tool-augmented agents; ready to scale into Airflow/LangGraph/Prefect).
Experience
Education
Key Strengths
- Built and deployed an AI meeting summarization system (summaries, action items, entities) with a Flask REST API
- Handles long-context constraints via chunking and hierarchical summarization
- Reduces hallucinated action items using NER + rule-based grounding constraints (verb/owner/sentence span)
- Evaluation-driven development using human validation against manually annotated notes; prioritizes precision over recall
- Designs modular, stateful AI agent workflows with guardrails and observable failure isolation
- Test-driven model/prompt selection using fixed eval sets, ablations, and task-specific metrics
- Translates non-technical stakeholder goals into prototypes and iterates to drive adoption
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