Muntabir Choudhury is a data scientist with a PhD in Computer Science and eight years of experience applying advanced AI, NLP, computer vision, and multimodal techniques to real-world problems. Her research and applied work span ETD document intelligence, LLM fine-tuning (LoRA/QLoRA), and production-grade deep learning pipelines, including multi-GPU training optimizations that halved compute time. She has a strong regulatory-data background from FDA projects—building LLM-driven decision tools and models that achieved up to 98% F1 for drug quality analysis—and a track record of turning book-length unstructured documents into structured, searchable corpora with near-perfect citation parsing. Comfortable moving models from research to deployment, she has implemented transfer learning, cross-attention multimodal classifiers, and metadata correction frameworks that notably improved indexing and retrieval. Based in Sterling, Virginia, she blends rigorous academic publication history with hands-on engineering—often optimizing infrastructure and scalability behind the scenes to make large-scale AI workflows practical.
8 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD Computer and Information Sciences General, Doctor of Philosophy - PhD Computer and Information Sciences General at Old Dominion University
Bachelor of Science - BS Computer Engineering, Bachelor of Science - BS Computer Engineering at Elizabethtown College
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