Summary
Maharshi Gor is a PhD candidate in Computer Science at the University of Maryland and a Graduate Teaching Assistant whose research advances Natural Language Understanding and Information Retrieval, with a focus on Question Answering, interpretability, and collaborative AI agents. He develops practical methods for profiling LLM-based agents and for building retrieval-augmented language models that balance parametric knowledge with real-time environment signals. With 11 years of industry and research experience, his background spans Google Research, Cohere, Contextual AI, and prior work in computer vision published at ICCV, AAAI, and WACV. He has contributed to high-impact NLP papers and served as a reviewer for top conferences including EMNLP, ACL, NeurIPS, and ICLR. Comfortable bridging theory and systems, he blends large-scale model analysis with applied engineering from earlier roles at Amazon and startups. Outside academia he enjoys strategic social-deception board games and Magic: The Gathering, a hobby that mirrors his interest in modeling complex multi-agent behavior.
11 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of Maryland
Bachelor of Technology (BTech) Computer Science, Bachelor of Technology (BTech) Computer Science at Visvesvaraya National Institute of Technology
English, Hindi