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Saptarshi Sengupta
Mid-level NLP/LLM Researcher specializing in question answering and retrieval-augmented generation
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About
Built ToolDreamer, a framework for selecting relevant tools for LLM agents by training a retriever on LLM-generated reasoning traces, and has hands-on experience building multi-agent systems in AutoGen (MAG-V) focused on question generation and tool-trajectory verification. Currently works as an AI-guides supervisor at Penn State, regularly communicating AI concepts to non-technical stakeholders.
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Key Strengths
- Designed and led development of a multi-agent framework (MAG-V) in AutoGen
- Strong retrieval-first approach (BM25 baseline → dense/LLM retrievers) with pragmatic model selection
- End-to-end evaluation mindset: bootstrapping datasets, synthetic augmentation, metric-based + qualitative analysis
- Performance/latency awareness and inference optimization using multi-GPU and reduced precision
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Experience
Education
Awards
Skills
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Publications
8 publications
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