Summary
Raghav Thind is a researcher and software engineer with four years of experience building AI-driven systems at the intersection of natural language, optimization, and human-centered analytics. He has developed practical frameworks that leverage LLM-powered agent pipelines, reinforcement learning, ensembling, and retrieval-augmented generation to translate natural-language problem descriptions into optimization solutions. His work in adversarial reinforcement learning and theory of mind at CMU focused on modeling trust and detecting deceptive behavior in multi-agent settings, while projects at UMD emphasized formalizing what-if and counterfactual analysis for visual analytics. Raghav also evaluated LLMs on undergraduate mathematics, creating a custom dataset and ordinal ranking methodology to probe model explanations and conceptual clarity. Based in College Park, MD, he blends rigorous statistical analysis with hands-on systems engineering and a visible curiosity for tooling and reproducible research.
4 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS Computer Science, Bachelor of Science - BS Computer Science at University of Maryland