Jane Hoffswell

764 total citations
25 papers, 439 citations indexed

About

Jane Hoffswell is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems. According to data from OpenAlex, Jane Hoffswell has authored 25 papers receiving a total of 439 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 8 papers in Artificial Intelligence and 4 papers in Information Systems. Recurrent topics in Jane Hoffswell's work include Data Visualization and Analytics (17 papers), Video Analysis and Summarization (5 papers) and Scientific Computing and Data Management (4 papers). Jane Hoffswell is often cited by papers focused on Data Visualization and Analytics (17 papers), Video Analysis and Summarization (5 papers) and Scientific Computing and Data Management (4 papers). Jane Hoffswell collaborates with scholars based in United States, Hong Kong and South Korea. Jane Hoffswell's co-authors include Jeffrey Heer, Arvind Satyanarayan, Ryan P. Russell, Zhicheng Liu, Jessica Schroeder, James Fogarty, Jasmine Zia, Chia-Fang Chung, Sean A. Munson and Wilmot Li and has published in prestigious journals such as IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum and Rare & Special e-Zone (The Hong Kong University of Science and Technology).

In The Last Decade

Jane Hoffswell

24 papers receiving 429 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jane Hoffswell United States 9 287 89 73 72 59 25 439
Bahador Saket United States 11 327 1.1× 151 1.7× 94 1.3× 85 1.2× 29 0.5× 23 500
Kleomenis Katevas United Kingdom 9 74 0.3× 230 2.6× 40 0.5× 51 0.7× 73 1.2× 19 435
José San Pedro Spain 8 215 0.7× 237 2.7× 66 0.9× 152 2.1× 206 3.5× 20 673
Heidi Lam Canada 10 370 1.3× 121 1.4× 67 0.9× 98 1.4× 104 1.8× 17 508
Khairi Reda United States 12 281 1.0× 78 0.9× 80 1.1× 39 0.5× 15 0.3× 35 438
Hanna Schäfer Germany 9 113 0.4× 178 2.0× 44 0.6× 27 0.4× 101 1.7× 26 444
Alper Sarıkaya United States 8 215 0.7× 115 1.3× 32 0.4× 29 0.4× 34 0.6× 11 392
Diana MacLean United States 9 53 0.2× 71 0.8× 59 0.8× 40 0.6× 126 2.1× 15 483
Michael G. Lamming United States 7 278 1.0× 57 0.6× 171 2.3× 45 0.6× 69 1.2× 9 496
Nitin Gupta India 7 72 0.3× 94 1.1× 31 0.4× 93 1.3× 85 1.4× 18 296

Countries citing papers authored by Jane Hoffswell

Since Specialization
Citations

This map shows the geographic impact of Jane Hoffswell'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 Jane Hoffswell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jane Hoffswell more than expected).

Fields of papers citing papers by Jane Hoffswell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jane Hoffswell. 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 Jane Hoffswell. The network helps show where Jane Hoffswell may publish in the future.

Co-authorship network of co-authors of Jane Hoffswell

This figure shows the co-authorship network connecting the top 25 collaborators of Jane Hoffswell. A scholar is included among the top collaborators of Jane Hoffswell 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 Jane Hoffswell. Jane Hoffswell is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Guo, Shunan, et al.. (2025). Utilizing Provenance as an Attribute for Visual Data Analysis: A Design Probe With ProvenanceLens. IEEE Transactions on Visualization and Computer Graphics. 31(10). 8452–8465. 2 indexed citations
2.
Hoffswell, Jane, et al.. (2024). How Aligned are Human Chart Takeaways and LLM Predictions? A Case Study on Bar Charts with Varying Layouts. IEEE Transactions on Visualization and Computer Graphics. 31(1). 536–546. 3 indexed citations
3.
4.
Rossi, Ryan A., Sana Malik, Jane Hoffswell, et al.. (2023). SpotLight: Visual Insight Recommendation. 19–23. 1 indexed citations
5.
Guo, Shunan, et al.. (2023). Socrates: Data Story Generation via Adaptive Machine-Guided Elicitation of User Feedback. IEEE Transactions on Visualization and Computer Graphics. 30(1). 1–11. 7 indexed citations
6.
Rossi, Ryan A., et al.. (2023). Dupo: A Mixed-Initiative Authoring Tool for Responsive Visualization. IEEE Transactions on Visualization and Computer Graphics. 30(1). 1–10. 5 indexed citations
7.
Rossi, Ryan A., Shunan Guo, Jane Hoffswell, et al.. (2023). A ML-based Approach for HTML-based Style Recommendation. 9–13. 1 indexed citations
8.
Agarwal, Shivam, Ryan A. Rossi, Fan Du, et al.. (2023). DataCockpit: A Toolkit for Data Lake Navigation and Monitoring Utilizing Quality and Usage Information. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 5305–5310. 2 indexed citations
9.
Hoffswell, Jane, Shunan Guo, Ryan A. Rossi, et al.. (2023). WhatsNext: Guidance-enriched Exploratory Data Analysis with Interactive, Low-Code Notebooks. 209–214. 1 indexed citations
10.
Hoffswell, Jane, et al.. (2022). ViSRE: A Unified Visual Analysis Dashboard for Proactive Cloud Outage Management. 27. 5–16. 1 indexed citations
11.
12.
Guo, Shunan, Jane Hoffswell, Ryan A. Rossi, et al.. (2022). Evaluating the Use of Uncertainty Visualisations for Imputations of Data Missing At Random in Scatterplots. IEEE Transactions on Visualization and Computer Graphics. 29(1). 1–11. 6 indexed citations
13.
Setlur, Vidya, et al.. (2022). Comparison Conundrum and the Chamber of Visualizations: An Exploration of How Language Influences Visual Design. IEEE Transactions on Visualization and Computer Graphics. 29(1). 1–11. 11 indexed citations
14.
Rossi, Ryan A., Jane Hoffswell, Shunan Guo, et al.. (2022). VisGNN: Personalized Visualization Recommendationvia Graph Neural Networks. Proceedings of the ACM Web Conference 2022. 2810–2818. 9 indexed citations
15.
Hoffswell, Jane, Wilmot Li, & Zhicheng Liu. (2020). Techniques for Flexible Responsive Visualization Design. 1–13. 36 indexed citations
16.
Hoffswell, Jane, Arvind Satyanarayan, & Jeffrey Heer. (2018). Augmenting Code with In Situ Visualizations to Aid Program Understanding. 1–12. 35 indexed citations
17.
Hoffswell, Jane, Alan Borning, & Jeffrey Heer. (2018). SetCoLa: High‐Level Constraints for Graph Layout. Computer Graphics Forum. 37(3). 537–548. 15 indexed citations
18.
Schroeder, Jessica, Jane Hoffswell, Chia-Fang Chung, et al.. (2017). Supporting Patient-Provider Collaboration to Identify Individual Triggers using Food and Symptom Journals. PubMed. 2017. 1726–1739. 85 indexed citations
19.
Hoffswell, Jane, Arvind Satyanarayan, & Jeffrey Heer. (2016). Visual Debugging Techniques for Reactive Data Visualization. Computer Graphics Forum. 35(3). 271–280. 20 indexed citations
20.
Satyanarayan, Arvind, Ryan P. Russell, Jane Hoffswell, & Jeffrey Heer. (2015). Reactive Vega: A Streaming Dataflow Architecture for Declarative Interactive Visualization. IEEE Transactions on Visualization and Computer Graphics. 22(1). 659–668. 171 indexed citations

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.

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