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Ankita Mungalpara
Mid-level Data Scientist specializing in Generative AI and multimodal systems
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About
Recent J&J intern who built a conversational RAG agent and led a shift from a monolithic model to a modular RAG workflow, cutting response time from several days to under a second by tackling data fragmentation, context retention, and embedding/latency optimization. Also worked on a large (7B-parameter) multimodal VQA pipeline for healthcare research and stays current via NeurIPS/ICLR and open-source contributions.
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Key Strengths
- Designed modular RAG workflow to replace monolithic approach
- Drove major latency improvement (from several days to under a second) for a conversational agent
- Strong understanding of deployment constraints for real-time/interactive systems (quantization, distillation, pruning)
- Built feedback loops for monitoring, evaluation, and iterative model improvement (retraining, A/B tests, versioning)
- Experience addressing data fragmentation and context retention in conversational systems
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Publications
1 publication
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