Jessica Hullman
- Computer Vision and Pattern Recognition top 0.5%
- Artificial Intelligence top 1%
- Sociology and Political Science top 5%
- Human-Computer Interaction top 2%
- Experimental and Cognitive Psychology top 5%
- Co-authors
- Nicholas DiakopoulosEytan AdarMatthew KayPriti ShahYea‐Seul KimSean A. MunsonAlex KaleZening Qu
- Topics
- Data Visualization and Analytics (48 papers)Advanced Text Analysis Techniques (16 papers)Explainable Artificial Intelligence (XAI) (12 papers)
- Journals
- NatureProceedings of the National Academy of SciencesSHILAP Revista de lepidopterología
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Jessica Hullman
71 papers receiving 2.5k citations
Peers
Comparison fields: 5 of 136
- Computer Vision and Pattern Recognition 1.6k
- Artificial Intelligence 944
- Sociology and Political Science 500
- Human-Computer Interaction 185
- Experimental and Cognitive Psychology 179
Countries citing papers authored by Jessica Hullman
This map shows the geographic impact of Jessica Hullman's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jessica Hullman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jessica Hullman more than expected).
Fields of papers citing papers by Jessica Hullman
This network shows the impact of papers produced by Jessica Hullman. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jessica Hullman. The network helps show where Jessica Hullman may publish in the future.
Co-authorship network of co-authors of Jessica Hullman
This figure shows the co-authorship network connecting the top 25 collaborators of Jessica Hullman. A scholar is included among the top collaborators of Jessica Hullman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jessica Hullman. Jessica Hullman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 7 | |
| 3 | 0 | |
| 4 | 27 | |
| 5 | 2 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 3 | |
| 9 | 4 | |
| 10 | 35 | |
| 11 | 154 | |
| 12 | Visual Reasoning Strategies and Satisficing: How Uncertainty Visualization Design Impacts Effect Size Judgments and Decisions. | 1 |
| 13 | 14 | |
| 14 | 21 | |
| 15 | 7 | |
| 16 | 70 | |
| 17 | 114 | |
| 18 | 159 | |
| 19 | 90 | |
| 20 | 96 |
About Jessica Hullman
Jessica Hullman is a scholar working on General Decision Sciences, Computer Vision and Pattern Recognition and Health Informatics, having authored 76 papers that have together received 2.6k indexed citations. Recurring topics across this work include Data Visualization and Analytics (48 papers), Advanced Text Analysis Techniques (16 papers) and Explainable Artificial Intelligence (XAI) (12 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.6k citations), General Decision Sciences (82 citations) and Human-Computer Interaction (185 citations). Jessica Hullman has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Nicholas Diakopoulos, Eytan Adar, Matthew Kay, Priti Shah, Yea‐Seul Kim, Sean A. Munson, Alex Kale, Zening Qu, Enrico Bertini and Steven Franconeri. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and SHILAP Revista de lepidopterología.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.