Chris Bryan
Assistant Professor in Computer Science
School of Computing and Augmented Intelligence
Arizona State University
Head of the Sonoran Visualization Laboratory (SVL @ ASU)
Quick Links
- For researchers and businesses interested in collaborating, see the Research page.
- Are you a student interested in Vis research? Read the Lab Policies page first!
- CV (last updated May 2026)
About
I am an Assistant Professor in the School of Computing and Augmented Intelligence at Arizona State University, which is located in the Ira A. Fulton Schools of Engineering at Arizona State University. I lead the Sonoran Visualization Laboratory (SVL @ ASU). I am also an affiliate faculty with ASU's Global Security Initiative. I received my Ph.D. from the University of California, Davis in 2018.
My research spans the areas of data visualization, human-computer interaction, augmented and virtual reality, and data science. Broadly, my lab develops novel algorithms, models, techniques, and interfaces that help humans work with and make sense of data. We regularly work with complex and real-world data, and develop advanced interactive visual analytics and data pipelines, including modeling and interpreting machine learning and artificial intelligence, and storytelling with data. See the Research page for more details, and the Publications page for our group's published papers.
External links
- iSearch (my ASU directory profile)
- experts.asu (my ASU expertise database fingerprint)
- Google Scholar
- DBLP
- Twitter (rarely updated...)
- Instagram (even more rarely updated...)
Recent News
May 2026
We'll have three paper at this year's EuroVis 2026, including an Honorable Mention for Engagement vs. Understanding: Comparing Immersive Virtual Reality and Desktop Displays for Climate Data Visualization. πππ
January 2026
We have three papers in this year's HICSS 2026: PatientLens, Developing The Strategists, and VizCoach. All three papers were led by MS students!
September 2025
We have one paper accepted to this year's IEEE VIS conference, by first year PhD student Zhuojun Jiang: The Hue-Man Factor: An Empirical Evaluation of Visualization Perception and Accessibility Across Color Vision Profiles
April 2025
We have two papers accepted to this year's EuroVis 2025 conference: Modeling and Measuring the Chart Communication Recall Process and VeCNA: Visual Exploration, Comparison and Analysis of Reconstructed Spatiotemporal Scientific Simulation Data.
We were awarded an Honorable Mention in this year's PacificVis Visual Data Storytelling Contest for our shortlisted entry entitled The Story of Wagyu: Bringing Charm of Japan's Pride to the World (link). ππ―π΅π
January 2025
We had two papers accepted this month: PromptAid: Visual Prompt Exploration, Perturbation, Testing and Iteration for Large Language Models has been accepted to IEEE Transactions in Visualization and Computer Graphics. This paper develops a human-in-the-loop pipeline to support iteratively prompting LLMs. Lost in Translation: How Does Bilingualism Shape Reader Preferences for Annotated Charts? has been accepted to CHI 2025. This study explores how presenting annotated text on top of visualizations in different languages (e.g., Arabic and Tamil) impacts reader preferences and cognition for users who are non-native English speakers.
December 2024
My former students Drs. Jinbin Huang and Anjana Arunkumar walked at the Fall 2024 Convocation (picture). Dr. Arunkumar also received the Dean's Dissertation Award. π This is the highest honor that can be bestowed on a graduating Ph.D. student in ASU's Fulton Schools of Engineering, and recognizes excellence in research, innovation, and potential for societal impact. Anjana was the only student from SCAI to receive this honor, and it is well deserved based on the fantastic work she did here in the SVL!
September 2024
Huge congratulations to Drs. Aditi Mishra and Jinbin Huang, who both successfully defended their dissertations this month! Dr. Mishra's dissertation, entitled Unlocking Artificial Intelligence: Interactive Visualizations for Novice Users to Explore, Understand, and Trust, and Dr. Huang's dissertation, entitled Understand AI and Go Beyond: Designing Interactive Visual Analytics Systems for Efficient Deep Learning Interpretability and Development, both develop several advanced techniques and tools for interrogating AI models and processes. π¨βπ» π π§ Dr. Mishra will soon join Fujitsu Research as a Research Scientist, and Dr. Huang will join Epsilon as a Data Scientist. Congratulations to both of you, and all your hard work in our group!!! π π π
We will have a paper at this year's International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD, co-located with Supercoputing 2024). The work, entitled Filling the Void: Data-Driven Machine Learning-Based Reconstruction of Sampled Spatiotemporal Scientific Simulation Data, is based on research Aditi conducted with scientists Los Alamos National Laboratory.
