Kelsey Urgo

Kelsey Urgo earned her PhD at the University of North Carolina at Chapel Hill. Before beginning her PhD program, she worked as a web developer at several institutions, including Wake Forest University and the Renaissance Computing Institute. Her research bridges the fields of information retrieval, human-computer interaction, and human-centered AI, exploring how search environments and generative AI tools can better support complex human tasks involving learning and creativity. She focuses on self-regulated learning, human-AI interaction, and developing and evaluating systems to align with human needs.

• Information retrieval
• Human computer interaction

• Search as learning
• Human-centered AI
• Interactive information retrieval 

• University of North Carolina at Chapel Hill, PhD, 2023
• University of California, Santa Cruz, BA, 2007

• Urgo, K., & Arguello, J. (2025). Search as Learning. Foundations and Trends® in Information Retrieval, 19(4), 365–556.

• Yang, Y., Urgo, K., Arguello, J., & Capra, R. (2025). Search+Chat: Integrating Search and GenAI to Support Users with Learning-oriented Search Tasks. Proceedings of the 2025 ACM SIGIR Conference on Human Information Interaction and Retrieval, 57–70

• Urgo, K., & Arguello, J. (2024). The Effects of Goal-setting on Learning Outcomes and Self-Regulated Learning Processes. Proceedings of the 2024 ACM SIGIR Conference on Human Information Interaction and Retrieval, 278–290

• Urgo, Kelsey, and Jaime Arguello. “Goal-Setting in Support of Learning During Search: An Exploration of Learning Outcomes and Searcher Perceptions.” Information Processing & Management, vol. 60, no. 2, p. 103158, Mar. 2023.
• Urgo, Kelsey, and Jaime Arguello. “Learning assessments in search-as-learning: A survey of prior work and opportunities for future research.” Information Processing & Management 59.2 (2022): 102821.