Melanie Tory
(she/her/hers)
Professor of the Practice
Research interests
- Visualization
- Human–computer interaction
- Human–AI interaction
Education
- PhD in Visualization, Simon Fraser University — Canada
Biography
Melanie Tory is a professor of the practice at the Khoury College of Computer Sciences at Northeastern University, based in Oakland.
Tory's research is in data visualization and human-AI interaction. Tory published in, and contributed to the organization of, IEEE VIS, IEEE TVCG, IEEE CG&A, and ACM CHI. Prior to joining Northeastern, she worked as a research scientist at Tableau Software.
Outside of work, Tory is passionate about the outdoors and enjoys hiking and kayaking.
Labs and groups
Recent publications
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The HEART Interface: Visualizing Risk Score Uncertainty in the Cardiothoracic ICU
Citation: Mahsan Nourani, Lien Nguyen, Carey Barry, Qingchu Jin, Melanie Tory. (2026). The HEART Interface: Visualizing Risk Score Uncertainty in the Cardiothoracic ICU IUI, 1019-1036. https://doi.org/10.1145/3742413.3789109 -
Stitching Meaning: Practices of Data Textile Creators
Citation: Sydney K. Purdue, Eduardo Puerta, Enrico Bertini, Melanie Tory. (2026). Stitching Meaning: Practices of Data Textile Creators IEEE Trans. Vis. Comput. Graph., 32, 725-735. https://doi.org/10.1109/TVCG.2025.3634255 -
Editorial: Guest Editors’ Introduction Special Issue on IEEE PacificVis 2025
Citation: Yingcai Wu, Melanie Tory, Ivan Viola. (2025). Editorial: Guest Editors' Introduction Special Issue on IEEE PacificVis 2025 IEEE Trans. Vis. Comput. Graph., 31, 3677-3678. https://doi.org/10.1109/TVCG.2025.3565832 -
Gridded Visualization of Statistical Trees for High-Dimensional Multipartite Data in Systems Genetics
Citation: Jane Lydia Adams, Robyn L. Ball, Jason A. Bubier, Elissa J. Chesler, Melanie Tory, Michelle A. Borkin. (2025). Gridded Visualization of Statistical Trees for High-Dimensional Multipartite Data in Systems Genetics Comput. Graph. Forum, 44. https://doi.org/10.1111/cgf.70113 -
Rethinking Human-AI Collaboration in Complex Medical Decision Making: A Case Study in Sepsis Diagnosis
Citation: Shao Zhang, Jianing Yu, Xuhai Xu, Changchang Yin, Yuxuan Lu , Bingsheng Yao, Melanie Tory, Lace M. K. Padilla, Jeffrey M. Caterino, Ping Zhang , Dakuo Wang. (2024). Rethinking Human-AI Collaboration in Complex Medical Decision Making: A Case Study in Sepsis Diagnosis CHI, 445:1-445:18. https://doi.org/10.1145/3613904.3642343 -
Struggles and Strategies in Understanding Information Visualizations
Citation: Maryam Rezaie, Melanie Tory, Sheelagh Carpendale. (2024). Struggles and Strategies in Understanding Information Visualizations IEEE Trans. Vis. Comput. Graph., 30, 3035-3048. https://doi.org/10.1109/TVCG.2024.3388560 -
Heuristics for Supporting Cooperative Dashboard Design
Citation: Vidya Setlur, Michael Correll, Arvind Satyanarayan, Melanie Tory. (2024). Heuristics for Supporting Cooperative Dashboard Design IEEE Trans. Vis. Comput. Graph., 30, 370-380. https://doi.org/10.1109/TVCG.2023.3327158 -
Investigating the Visual Utility of Differentially Private Scatterplots
Citation: Liudas Panavas, Tarik Crnovrsanin, Jane Lydia Adams, Jonathan R. Ullman, Ali Sarvghad, Melanie Tory, Cody Dunne. (2024). Investigating the Visual Utility of Differentially Private Scatterplots IEEE Trans. Vis. Comput. Graph., 30, 5370-5385. https://doi.org/10.1109/TVCG.2023.3292391 -
Untidy Data: The Unreasonable Effectiveness of Tables
Citation: Bartram, Lyn, Michael Correll, and Melanie Tory. "Untidy data: The unreasonable effectiveness of tables." IEEE Computer Graphics and Applications, (2021). -
The Unmet Data Visualization Needs of Decision Makers within Organizations
Citation: Evanthia Dimara, Harry Zhang, Melanie Tory, and Steven Franconeri, The Unmet Data Visualization Needs of Decision Makers within Organizations, IEEE Transactions on Visualization and Computer Graphics, 2021.
Related news
Current PhD students
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Carey Barry
PhD Student
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Aditi Krishna
PhD Student
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Shani Spivak
PhD Student
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Timothy Yim
PhD Student
