Jane Hoffswell

Research Scientist

Seattle

Jane is a research scientist at Adobe, specializing in visualization and human-computer interaction (HCI). Her research focuses on responsive visualization, visualizations for system and code understanding, and the design of interactive, end-user systems. Jane received her Ph.D. in Computer Science from the University of Washington in 2020, where she was advised by Prof. Jeffrey Heer as part of the Interactive Data Lab. Before that, she graduated from Harvey Mudd College with a B.S. in Computer Science.

For an up-to-date list of publications, please refer to her personal website.

Publications

How Aligned are Human Chart Takeaways and LLM Predictions? A Case Study on Bar Charts with Varying Layouts

Wang, H., Hoffswell, J., Thane, S., Bursztyn, V., Bearfield, C. (Oct. 13, 2024)

IEEE VIS 2024

Representing Charts as Text for Language Models: An In-Depth Study of Question Answering for Bar Charts

Bursztyn, V., Hoffswell, J., Guo, S., Koh, E. (Oct. 13, 2024)

IEEE VIS 2024 (short paper)

Interaction Techniques for Exploratory Data Visualization on Mobile Devices

Snyder, L., Rossi, R., Koh, E., Heer, J., Hoffswell, J. (May. 27, 2024)

EuroVis 2024 (short paper)

Dupo: A Mixed-Initiative Authoring Tool for Responsive Visualization

Kim, H., Rossi, R., Hullman, J., Hoffswell, J. (Oct. 23, 2023)

IEEE VIS 2023

Socrates: Data Story Generation via Adaptive Machine-Guided Elicitation of User Feedback

Wu, G., Guo, S., Hoffswell, J., Chan, G., Rossi, R., Koh, E. (Oct. 23, 2023)

IEEE VIS 2023

PaperToPlace: Transforming Instruction Documents into Spatialized and Context-Aware Mixed Reality Experiences

Chen, C., Nguyen, C., Hoffswell, J., Healey, J., Bui, T., Weibel, N. (Oct. 10, 2023)

ACM UIST 2023

WhatsNext: Guidance-enriched Exploratory Data Analysis with Interactive, Low-Code Notebooks

Chen, C., Hoffswell, J., Guo, S., Rossi, R., Chan, G., Du, F., Koh, E., Liu, L. (Oct. 3, 2023)

IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)

DataPilot: Utilizing Quality and Usage Information for Subset Selection during Visual Data Preparation

Narechania, A., Du, F., Sinha, A., Rossi, R., Hoffswell, J., Guo, S., Koh, E., Navathe, S., Endert, A. (Apr. 23, 2023)

CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, April 2023

Comparison Conundrum and the Chamber of Visualizations: An Exploration of How Language Influences Visual Design

Gaba, A., Setlur, V., Srinivasan, A., Hoffswell, J., Xiong, C. (Oct. 18, 2022)

IEEE VIS 2022

Let’s Get Personal: Exploring the Design of Personalized Visualizations

Bullock, B., Guo, S., Koh, E., Rossi, R., Du, F., Hoffswell, J. (Oct. 18, 2022)

IEEE VIS 2022 (short paper)

ViSRE: A Unified Visual Analysis Dashboard for Proactive Cloud Outage Management

Kayongo, P., Hoffswell, J., Saini, S., Garg, S., Koh, E., Wang, H., Jacobs, T. (Oct. 2, 2022)

IEEE Working Conference on Software Visualization (VISSOFT)

Cicero: A Declarative Grammar for Responsive Visualization

Kim, H., Rossi, R., Du, F., Koh, E., Guo, S., Hullman, J., Hoffswell, J. (May. 2, 2022)

ACM Human Factors in Computing Systems (CHI)

An Evaluation-Focused Framework for Visualization Recommendation Algorithms

Zeng, Z., Moh, P., Du, F., Hoffswell, J., Lee, T., Malik, S., Koh, E., Battle, L. (Oct. 26, 2021)

Best Paper Honorable Mention

IEEE VIS 2021

Techniques for Flexible Responsive Visualization Design

Hoffswell, J., Li, W., Liu, L. (Apr. 27, 2020)

Best Paper

ACM Human Factors in Computing Systems (CHI)

Interactive Repair of Tables Extracted from PDF Documents on Mobile Devices

Hoffswell, J., Liu, L. (May. 2, 2019)

ACM Human Factors in Computing Systems (CHI)

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