Angus G. Forbes
Biography: Angus Forbes is an Associate Professor in the Computer Graphics Technology Department. His interdisciplinary research in computational media focuses on topics in graphics and visualization, and recent projects from my lab include the creation of interactive tools for visualizing large simulation datasets, bio-inspired approaches to data reconstruction, and neural rendering architectures for temporally stable real-time denoising and supersampling. He is interested in designing interfaces and developing interaction techniques that augment our ability to reason about complex datasets and to facilitate effective data analysis. He is also engaged in exploring the creative use of technologies in order to enable new forms of artistic expression and to provide critical perspectives into the sociotechnical systems that govern contemporary life. He received his PhD and MS degrees from University of California, Santa Barbara.
Research keywords: Visualization, graphics, data science, computational art, creative coding
Yingjie Victor Chen
Personal website: https://polytechnic.purdue.edu/profile/chen489
Purdue Intelligent Visualization and Interaction Lab: https://va.tech.purdue.edu/
Biography: Yingjie Victor Chen is an Associate Professor of Computer Graphics Technology. Aiming to augment human cognition to help users explore and utilize the digital world, Dr. Chen’s research bridges multiple HCI domains to discover novice interactions and visualizations supporting users’ reasoning, problem-solving, learning, and decision making. He received his Ph.D. and master's degree in Information Technology from Simon Fraser University, Canada. He has a Bachelor's degree in Engineering from Tsinghua University, China.
Research keywords: Information visualization, human-computer interaction, visual analytics, virtual reality
Personal website: https://polytechnic.purdue.edu/profile/tmcgraw
Biomedical Imaging & Graphics (BIG) Lab: https://web.ics.purdue.edu/~tmcgraw/
Biography: Tim McGraw is an Associate Professor of Computer Graphics Technology. His areas of interest are virtual reality, scientific visualization, real-time computer graphics, medical image processing and computational art. Specific projects include modeling and mesh editing in VR, diffusion tensor MRI (DT-MRI) visualization, and mesh processing. He was awarded 4 patents related to DT-MRI visualization projects performed with Siemens Corporate Research. He has previous industry experience as a mechanical engineer and as a game developer (Electronic Arts, Schell Games, Rainbow Studios). He received his Ph.D. in Computer and Information Science and Engineering from the University of Florida.
Research keywords: Scientific visualization, tensor fields, vector fields, medical images, virtual reality
Vetria L. Byrd
Personal website: https://polytechnic.purdue.edu/profile/vbyrd
Byrd Data Vis Lab: https://byrdvislab.wixsite.com/website
Biography: Vetria Byrd is an assistant professor of Computer Graphics Technology. Her research is in the areas of data visualization pedagogy, visualization of heterogeneous data and the utilization of data visualization and data science to advance the study, detection and diagnosis of systemic lupus erythematosus (aka, lupus). She holds advanced degrees from The University of Alabama at Birmingham: PhD in computer science, master’s degrees in biomedical engineering and computer science and a BS in Computer Science. She is the founder and organizer of BPViz: Broadening Participation in Visualization Workshops (@BPViz), a Superhero of Science (https://youtu.be/S4_MVmQDLRk ) and an “Agent of Insight.”
Research keywords: Information visualization, data science, data visualization pedagogy, data visualization capacity, data visualization literacy, broadening participation
Paul C. Parsons
Personal website: https://paulcparsons.com
Design, Visualization, & Cognition (DVC) Lab: https://www.dvclab.net
Biography: Paul Parsons is an associate professor of Computer Graphics Technology. His research is in the area of human-computer interaction, with a focus on the design and use of interactive visualization interfaces. His lab is currently researching 3 main topics: i) data visualization design practice; ii) cognitive aspects of visualization use; and iii) user experience for scientific cyberinfrastructure. He does some research in other areas, including design education and learning technologies. He holds a PhD in computer science (University of Western Ontario, 2013) and a BS in computing and cognitive science (Queen’s University at Kingston, 2007).
Research keywords: Design practice, design cognition, visual reasoning, cognitive systems, user experience
- Thomas, M.M. Liktor, G., Peters, C., Kim, S., Vaidyanathan, K., & Forbes, A.G. (2022). Temporally Stable Real-Time Joint Neural Denoising and Supersampling. Proceedings of the ACM in Computer Graphics and Interactive Techniques. 10.1145/3543870. [PDF]
- Abramov, D., Burchett, J.N., Elek, O., Hummels, C., Prochaska, J.X., & Forbes, A.G. (2022). CosmoVis: An Interactive Visual Analysis Tool for Exploring Hydrodynamic Cosmological Simulations. IEEE Transactions on Visualization and Computer Graphics. 10.1109/TVCG.2022.3159630. [PDF]
- Elek, O., Burchett, J.N., Prochaska, J.X., & Forbes, A.G. (2022). Monte Carlo Physarum Machine: Characteristics of Pattern Formation in Continuous Stochastic Transport Networks. Artificial Life. 10.1162/artl_a_00351. [PDF]
- Elek, O., Burchett, J.N., Prochaska, J.X., & Forbes, A.G. (2021). Polyphorm: Structural Analysis of Cosmological Datasets via Interactive Physarum Polycephalum Visualization. IEEE Transactions on Visualization and Computer Graphics. 10.1109/TVCG.2020.3030407. [PDF]
- Parsons, P. (2021). Understanding Data Visualization Design Practice. IEEE Transactions on Visualization and Computer Graphics, (Proc. IEEE VIS ’21). 10.1109/TVCG.2021.3114959. [PDF]
- Byrd, V. & Dwenger, N. (2021), "Activity Worksheets for Teaching and Learning Data Visualization," in IEEE Computer Graphics and Applications, https://doi.org/10.1109/MCG.2021.3115396.
- Byrd, V. L. (2021), Innovative Pedagogy for Teaching and Learning Data Visualization Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. https://peer.asee.org/37342
- Zhao, J., Liu, X., Chen, G., Qian, Z. Y., & Chen, Y. V. (2021). Phoenixmap: An Abstract Approach to Visualize 2D Spatial Distributions. Transactions on Visualization and Computer Graphics, 27(03), 2000-2014. doi: 10.1109/TVCG.2019.2945960
- Byrd V.L. (2021) Using Dear Data Project to Introduce Data Literacy and Information Literacy to Undergraduates. In: Arabnia H.R., Deligiannidis L., Tinetti F.G., Tran QN. (eds) Advances in Software Engineering, Education, and e-Learning. Transactions on Computational Science and Computational Intelligence. Springer, Cham. https://doi.org/10.1007/978-3-030-70873-3_10
- Thomas, M.M., Vaidyanathan, K., Liktor, G., & Forbes, A.G. (2020). A Reduced-Precision Network for Image Reconstruction. ACM Transactions on Graphics. 10.1145/3414685.3417786. [PDF]
- Parsons, P. Gray, C. M., Baigelenov, A., & Carr, I. (2020). Design Judgment in Data Visualization Practice. IEEE Visualization Conference (IEEE VIS ’20). 10.1109/VIS47514.2020.00042. [PDF]
- Parsons, P., & Shukla, P. (2020). Data Visualization Practitioners’ Perspectives on Chartjunk. IEEE Visualization Conference (IEEE VIS ’20). 10.1109/VIS47514.2020.00049. [PDF]
- McGraw, T., High-quality real-time raycasting and raytracing of streamtubes with sparse voxel octrees. IEEE Visualization, 2020.
- Zheng, A., & Byrd, V. L. (2020, October). Students’ Perception of a Method for Identifying Topics for Research Questions. In 2020 IEEE Frontiers in Education Conference (FIE) (pp. 1-8). IEEE.
- Kanter, N. R., & Byrd, V. L. (2020, October). A Method for Transforming a Broad Topic to a Focused Topic for Developing Research Questions. In 2020 IEEE Frontiers in Education Conference (FIE) (pp. 1-7). IEEE.
- Forbes, A.G. (2019). Creative AI: From Expressive Mimicry to Critical Inquiry. Artnodes. 10.7238/a.v0i26.3370. [PDF]
- Tang, H., Wei, S., Zhou, Z., Qian, Z. Y., & Chen, Y. V. (2019). TreeRoses: Outlier-Centric Monitoring and Analysis of Periodic Time Series Data. Journal of Visualization. Published. https://doi.org/10.1007/s12650-019-00586-1
- Parsons, P. (2018). Conceptual Metaphor Theory as a Foundation of Communicative Visualization Design. IEEE VIS Workshop of Visualization for Communication (VisComm). Berlin, Germany. [PDF]
- Parsons, P. (2018). Promoting Representational Fluency for Cognitive Bias Mitigation in Information Visualization. In: Ellis, Geoffrey (Ed.): Cognitive Biases in Visualizations, pp. 137–147. [PDF]
- Li, M.G*, Wu, W.G, Zhao, J.G, Perkis, D., Bond, T. N., Mumford, K., Hummels, D. L., & Chen, Y. V. (2018). CareerVis: Hierarchical Visualization of Career Pathway Data. IEEE Computer Graphics and Applications, 38(6), 96-105.
- Chen, Y., Huynh, W., McGraw, T., Qian, Z., and Hassan, R., Unobtrusive touch‐free interaction on mobile devices in dirty working environments. Human Factors and Ergonomics in Manufacturing & Service Industries 28, no. 5, 250-259, 2018.
- McGraw, T., Guayaquil-Sosa, A., Hybrid Rendering for Medical Image Atlas Visualization, Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2017.
- Zheng, H., Adamo-Villano, N., McGraw, T., Griggs, R., Using Computer Animation for Emergency Medicine Education. International Journal of Technology Enhanced Learning, 2017
- Promann, M., Wei, S., Qian, C.Z., and Y.V. Chen (2016), "The Role of Aesthetics and Perception in Raising Situation Awareness: Lessons from SpringRain", International Journal of Human-Computer Interaction (IJHCI), DOI: 10.1080/10447318.2016.1140951
Herring, D., McGraw, T., Inter-color NPR Lines: A Comparison of Rendering Techniques. The Computer Games Journal, 5(1), 39-53, 2016.
Byrd, V. L. (2021), "Innovative Pedagogy for Teaching and Learning Data Visualization," In Proceedings of 2021 ASEE Virtual Annual Conference https://peer.asee.org/37342
Byrd, V. L. & Camba, J. D. (2020, October), "A Worksheet Method for Developing Research Questions: An Examination of Three Graduate Student Cohorts," In Proceedings of 2020 IEEE Frontiers in Education (FIE) Conference, 1 - 7. https://doi.org/10.1109/FIE44824.2020.9273883
Byrd, V. L. & Asunda, P. (2020, October), "Using Evidence Based Practices and Learning to Enhance Critical Thinking Skills in Students Through Data Visualization," In Proceedings of American Society for Engineering Education (ASEE) https://doi.org/10.18260/1-2--35438
Byrd, V. (2019), "Using Bloom's Taxonomy to Support Data Visualization Capacity Skills," [Best Paper Award], In Proceedings of E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, 1039 - 1053. New Orleans, Louisiana, United States: Association for the Advancement of Computing in Education (AACE). https://www.learntechlib.org/primary/p/21809/
Vieira, C., Parsons, P., & Byrd, V. (2018), "Visual learning analytics of educational data: a systematic literature review and research agenda," Computers & Education, 122, 119-135.
Byrd, V. L., & Vieira, C. (2017, June), "Visualization: a conduit for collaborative undergraduate research experiences," In Proceedings of American Society for Engineering Education (ASEE) https://doi.org/10.18260/1-2--29108
Barvo, E. G., Burbano, A., Byrd, V. L., & Forbes, A. G. (2017), "The Interactive Image: A media archaeology approach," Leonardo 50 (4), 368-375.
Byrd, V. (2018), "Special Snapshot Section: Making a Case for Data Visualization at the Undergraduate Level," Journal of Purdue Undergraduate Research, 8(1), 26.
Periasamy, P. & Byrd, V. L. (2019, July), "Generative adversarial networks for lupus diagnostics," PEARC '19: Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machine (Learning), 104, 1-8. https://doi.org/10.1145/3332186.3338102
Byrd, V. L. (2019), "Facilitating Deep Learning Through Vertical Integration Between Data Visualization Courses Within an Undergraduate Data Visualization Curriculum," International Conference on Human-Computer Interaction, 193-201. https://doi.org/10.1007/978-3-030-23525-3_25
Byrd, V., & Camba, J.D. (2020, June), "Design Activity Worksheets for Developing Research Questions," In Proceedings of American Society for Engineering Education (ASEE), https://doi.org/10.18260/1-2--34384
Bosman, L., Madamanchi, A., Bartholomew, S., & Byrd, V. (2020), "Applying Artificial Intelligence to the Beer Game," In Proceedings of American Society for Engineering Education (ASEE) Virtual Conference. Best Paper. https://doi.org/10.18260/1-2--34156
Santana, V., Bartholomew, S., Rowe, W., Byrd, V., Strimel, G., & Han, K. (2020), "SMART buoys: integrating data visualization and design to reduce ocean-life casualties," Technology and Engineering Teacher, 79 (8), 19-23.
Bartholomew, S., Strimel, G., Byrd, V., Santana, V., Otto, J., Laureano, Z., & Derome, B. (2020), "Using data to improve precision in crop fertilization through digital agriculture," Technology and Engineering Teacher, 79 (7), 32-36.
- Parsons (2022). NSF: CAREER: Supporting Data Visualization Design Practice. May 2022 - April 2027. $524,222. [NSF Page]
- Byrd (2021). HDR Institute: Geospatial Institute for Digital Innovation to Enhance Resilience and Sustainability, October 1, 2021 - September 30, 2026, Total Award Amount: $15M; Sub-award to Purdue: $2.5M; Byrd Amount: $294,000. NSF Award #2118329, [Announcement]
- Tim McGraw, Michael Eddy, First place in the 2021 IEEE SciVis Contest, “Hybrid rendering for interactive visualization of mantle convection”
- Zuotian Li et.al, Honorable Mention for Effective Visual Design and Academic Outreach, IEEE VAST Challenge 2021, “CloudAnnotator: Clustering and Annotating Streaming Text Data”
- Prince Owusu Attah et.al, Award for Effectively Transforming Task Decomposition into Conceptual Design, IEEE VAST Challenge 2020
- Career Mapping Visualization System - https://va.tech.purdue.edu/careerVis/