Cecilia Aragon is a professor in the department of Human Centered Design & Engineering (HCDE) and a member of the eScience Institute at the University of Washington, where she directs the Human-Centered Data Science Lab. Her research focuses on human-centered data science, which concerns itself with both the algorithms and the highly interwoven and multifaceted interactions among individuals, society, and technology that are catalyzed by the enormous growth in data that characterizes the current age.

Aragon's research group develops software to facilitate insight into vast and complex data sets, incorporating techniques such as visual analytics (visualization and machine learning), data science, ethnography, and the study of sociotechnical systems including informal text communication and social media. Other projects include the use of computer gaming for collaborative science learning, and topics related to usability and sustainability.

Her early work was in theoretical computer science. She was the co-inventor (with Raimund Seidel) of the treap, a binary search tree in which each node has both a key and a priority, and the randomized search tree, which uses random priorities in treaps to achieve good average-case performance. With Johnson, McGeoch, and Schevon, she conducted the first extensive evaluation of the simulated annealing algorithm in combinatorial optimization problems.