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Faculty
Hannah Bako
Assistant Professor of Data Science
School of Data Science
Email: znf3ft@virginia.edu
Additional Contact Information
Website: hannahbako.github.io/
Office: 1919 Ivy Rd., Rm. 332
LinkedIn: https://www.linkedin.com/in/hannah-bako/
Pronouns: she/her
Hannah Bako is a researcher exploring how to inspire and support creativity in data visualization design.
Her work sits at the intersection of data visualization, human-computer interaction, and design, combining empirical studies with tool development to investigate how people conceptualize and implement design ideas. She examines how designers work with code, interact with examples, and engage with AI-powered systems. Using these insights, she creates tools that enable expressive, context-aware, and diverse visualizations. Her research bridges foundational studies of visualization behavior with practical systems that enhance the design process and strengthen visual communication.
Bako holds a Ph.D. in Computer Science from the University of Maryland, College Park, an M.Sc. in Software Engineering from Stevens Institute of Technology, and a B.Sc. in Computer Information Systems from Babcock University.
Education
- Ph.D. in Computer Science, University of Maryland, College Park
- M.Sc. in Software Engineering, Stevens Institute of Technology
- B.Sc. in Computer Information Systems, Babcock University
Data Science Domains
Design
Areas of Practice
Human-Centered Design and Interaction
Selected Publications
H. K. Bako, X. Liu, G. Ko, H. Song, L. Battle and Z. Liu, "Unveiling How Examples Shape Visualization Design Outcomes," in IEEE Transactions on Visualization and Computer Graphics, vol. 31, no. 1, pp. 1137-1147, Jan. 2025, doi: 10.1109/TVCG.2024.3456407.
H. K. Bako, X. Liu, L. Battle and Z. Liu, "Understanding how Designers Find and Use Data Visualization Examples," in IEEE Transactions on Visualization and Computer Graphics, vol. 29, no. 1, pp. 1048-1058, Jan. 2023, doi: 10.1109/TVCG.2022.3209490.
H. K. Bako, A. Bhutani, X. Liu, K. A. Cobbina and Z. Liu, "Evaluating the Semantic Profiling Abilities of LLMs for Natural Language Utterances in Data Visualization," 2024 IEEE Visualization and Visual Analytics (VIS), St. Pete Beach, FL, USA, 2024, pp. 261-265, doi: 10.1109/VIS55277.2024.00060.
Hannah K. Bako, Alisha Varma, Anuoluwapo Faboro, Mahreen Haider, Favour Nerrise, Bissaka Kenah, John P Dickerson, and Leilani Battle. 2023. User-Driven Support for Visualization Prototyping in D3. In Proceedings of the 28th International Conference on Intelligent User Interfaces (IUI '23). Association for Computing Machinery, New York, NY, USA, 958–972. https://doi.org/10.1145/3581641.3584041
H. Bako et al., "Streamlining Visualization Authoring in D3 Through User-Driven Templates," 2022 IEEE Visualization and Visual Analytics (VIS), Oklahoma City, OK, USA, 2022, pp. 16-20, doi: 10.1109/VIS54862.2022.00012