Vedant Somani is a Text Mining Student Specialist at the eScience Institute and a Master’s student in Information Management at the University of Washington. His work focuses on applying data science and machine learning to extract insights from complex textual data, with an emphasis on building practical, scalable solutions. He brings a strong foundation in software engineering and has experience developing end-to-end systems, from data collection and processing to analysis and deployment. He is also interested in agentic AI systems and how intelligent workflows can automate and enhance research tasks.
Before joining eScience, Vedant worked across machine learning and full-stack development roles, where he built reliable systems to solve real-world problems. He enjoys collaborating with researchers to translate open-ended questions into structured, data-driven approaches, and aims to make text mining more accessible and useful across disciplines.