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Ananya Dandi
Junior Machine Learning Researcher specializing in knowledge distillation
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About
Built and shipped LLM-powered agents including a production RAG research assistant that cut research lookup time from ~20 minutes to ~10–20 seconds using caching, retrieval thresholds, and citation-enforced grounded answers. Also designed multi-step, tool-calling workflows with stateful critique/revision loops and pragmatic monitoring (retry/schema-failure/low-confidence signals) plus normalization/validation layers for messy notes/spreadsheet-style data.
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Key Strengths
- Shipped production RAG research assistant with guardrails, caching, and failure-mode handling
- Designed grounded-answering safeguards (context-only answers, 'I don't know' fallback, citation-based confidence)
- Measured and delivered large workflow time reduction (manual ~20 minutes to ~10–20 seconds)
- Built multi-step agent workflows with critique/revision loops and capped iterations to avoid infinite loops
- Implemented practical eval/monitoring loops (offline prompt sets; online signals like retry rate, schema failures, low confidence)
- Handled messy multi-source data via normalization, validation, and safe-action gating with clarification fallbacks
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