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, 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. “Capturing Self-Regulated Learning During Search.” 3rd International Workshop on Investigating Learning during Web Search co-located at SIGIR hybrid conference. 2022.
• Smith, Catherine, Kelsey Urgo, Jaime Arguello, and Robert Capra. “Learner, Assignment, and Domain: Contextualizing Search for Comprehension.” In ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR ’22). 2022. 
• Urgo, Kelsey, and Jaime Arguello. “Understanding the “Pathway” Towards a Searcher’s Learning Objective.” ACM Transactions on Information Systems (TOIS) 40.4 (2022): 1-42.
• 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.