Scholar
Tao Long
Google Scholar ID: x6REPHkAAAAJ
Columbia University
Citations & Impact
Citations
365
H-index
7
i10-index
7
Publications
16
Co-authors
35
list available
Publications
Resume (English only)
Academic Achievements
- Published multiple papers covering topics such as building trust with proactive AI, delivering ambient commentary, measuring perceptions and behavioral effects of minoritized anthropomorphic cues in LLMs, and the utility and customization of an AI workflow over time.
Research Experience
- Involved in several research projects such as DoubleAgents, FeedQUAC, and has organized workshops, including one on Facilitating Longitudinal Interaction Studies of AI Systems at UIST 2025.
Education
- Earned his bachelors with Summa Cum Laude from Cornell University; currently a PhD student in Computer Science at Columbia University, advised by Professor Lydia Chilton.
Background
- A fourth-year Computer Science PhD student at Columbia University, with a focus on human-computer interaction (HCI). His research focuses on making generative AI models more usable, useful, and well-integrated into our everyday workflows. Specifically, he designs and builds human-AI and agentic workflows that reduce cognitive load and manual effort, support diverse exploration and fast iterations, and integrate seamlessly into existing users' practices.
Miscellany
- Looking for Summer 2026 Research Internships; personal interests include travel.
