Tao Long
Research Intern
About
Tao Long (cs.columbia.edu/~long (opens in new tab)) is a fourth-year CS PhD student at Columbia University, advised by Lydia Chilton. This summer, Tao is working with Microsoft Research NYC – AI Frontiers, collaborating with Weili Shi, Hussein Mozannar, Maya Murad, Cheng Tan, and Rafah Hosn.
Tao’s research in human-computer interaction (HCI) explores how people collaborate and align with AI systems and agents over time, with the goal of making AI tools more usable, useful, trustworthy, and seamlessly integrated into everyday productivity practices. He builds and evaluates human-AI and agentic systems that reduce cognitive and temporal effort on complex daily tasks and offload work to AI while preserving human ownership and authenticity for writers, developers, designers, and event planners. His work spans agentic AI workflows grounded in cognitive science and communication theories, longitudinal evaluation of AI tools, and proactive yet still ambient human-AI experiences. Tao is a recipient of the 2025-2026 Capital One AI PhD Fellowship. Before his PhD, Tao earned a BS Summa Cum Laude from Cornell University.