By By Kelly deVos
Publication Date: 2026-04-30 22:09:00
Modern medicine runs on data organized into tables and charts that help doctors make fast, informed decisions. Survival rates and prescription side effects are often distilled into formats that can be scanned in seconds. But that clarity doesn’t come easily. The data must be extracted and organized, often through a time-consuming process that can leave critical information buried deep in research reports.
Naman Ahuja wants to change that.
This May, Ahuja will graduate from the School of Computing and Augmented Intelligence, part of the Ira A. Fulton Schools of Engineering at Arizona State University, earning a master’s degree in computer science.
Over the past two years, his research has focused on how to get artificial intelligence, or AI, systems to convert long, unstructured text into accurate, usable tables. This spring, that work earned him an IBM Infrastructure Master’s Fellowship Award, a prestigious honor that recognizes research with strong real-world and…