Kuldeep Singh is a data scientist and NLP specialist with nine years of professional experience and a master's-level education from Michigan State University. He has applied LLMs and advanced prompting techniques in production-focused research, most recently improving retrieval and reasoning for a financial QA system at JPMorgan Chase using novel clustering-based negative sampling. At ConcertAI he built generalizable NLP pipelines to extract and normalize medication data from unstructured EHRs, combining NER, relation extraction, and entity linking. Proficient in Python, PyTorch, Keras, and scikit-learn, he pairs engineering rigor with research curiosity and a knack for practical prompting strategies. Based in East Lansing, he balances strong academic performance with hands-on projects that bridge research and deployable solutions. He’s a lifelong learner and collaborator who seeks opportunities to turn complex data problems into actionable insights.
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