Ryan Mullins researches and develops human-AI teams, with an interest in the experiences enabling human-AI collaboration. His research combines methods and concepts from the visual analytics, computer science, and cognitive systems engineering domains to create novel ways for human and AI actors to collaborate and solve complex problems. Ryan has applied his skills in the command and control, information analysis, and cybersecurity domains, among others. Additionally, Ryan manages the Division’s portfolio of data science platforms, shaping their capability roadmaps and evangelizing their use across the company.
Ryan holds an MS in Geography and BS in Computer Science from the Pennsylvania State University. He is a member of the North American Cartographic Information Society, the Association for Computing Machinery, and the United States Geospatial Intelligence Foundation.
Mullins, R., Fouse, A., Ganberg, G., & Schurr, N. (2020, January). Practice Makes Perfect: Lesson Learned from Five Years of Trial and Error Building Context-Aware Systems. In Proceedings of the 53rd Hawaii International Conference on System Sciences.
Mullins, R.S., Ford, B., Kemmet, L., & Weissman, S. (2019). The Civil Affairs Information Matrix: Designing Context-Aware Visual Analytics Enabling Mission Planning with Ensemble Learning. In International Conference on Intelligent Human Systems Integration (pp. 491-496). Springer, Cham.
Fegley, B. D., Mullins, R., Ford, B., & Weiss, C. (2018, July). LineChange: An Analytic Framework for Automated Moderation of Crowdsourcing Systems. In International Conference on Human-Computer Interaction (pp. 401-408). Springer, Cham.
Fouse, A., Mullins, R. S., Ganberg, G., & Weiss, C. (2017). The Evolution of User Experiences and Interfaces for Delivering Context-Aware Recommendations to Information Analysts. In International Conference on Applied Human Factors and Ergonomics (pp. 15-26). Springer, Cham.
Fouse, A., Mullins, R.S., & Ziemkiewicz, C. (2016). A Framework for Context-Aware Visualization in Cyber Defense. In Proceedings of the 2016 IEEE Symposium on Visualization for Cyber Security. Baltimore, MD, USA.
Mullins, R. S., Fouse, A., McCormack, R., & Pfautz, S. L. (2015). A context-aware decision support tool for assessing and mitigating drivers of civil instability. Procedia Manufacturing, 3, 4115-4120.
For more information about Ryan Mullin’s publications, please contact email@example.com.