Program

Keynote

Dr. Lars Linsen [University of Münster, Germany]

Title: Quantifying and Communicating Uncertainty in Visual Data Analysis: Approaches and Challenges

Abstract: Visualization is concerned with the analysis of collected data from measurements or of generated data from mathematical models. Hence, aleatoric (or data) uncertainty as well as epistemic (or model) uncertainty are inherently present in the analysis process. A trustworthy visual data analysis shall quantify and communicate the uncertainty during the visual data analysis approach. In this talk, challenges in estimating and conveying uncertainties will be identified and exemplified. Topics include ensemble approaches, statistical considerations, and machine-learning models.

Bio: Lars Linsen is a Full Professor of Computer Science at the University of Münster, Germany, where he is leading the Visualization and Graphics group (VISIX). He received his academic degrees in Computer Science from the University of Karlsruhe, Germany, including a Ph.D. degree in 2001. Further steps in his career include academic positions at the University of California, Davis, U.S.A., the University of Greifswald, Germany, and the Jacobs University, Bremen, Germany. His research interests are in scientific visualization, medical visualization, and multivariate data visualization, which include aspects of uncertainty visualization.

Paper Presentations

Each full paper presentation will be 10 mins including Q&A. Each short paper presentation will be for 8 mins including Q&A.

¹Xiaohan Wang, Zhimin Li, Joshua A Levine, and Matthew Berger, "Seeing the Many: Exploring Parameter Distributions Conditioned on Features in Surrogates" [Full paper, 2:45pm-2:55pm].

²Daniel Klötzl, Ozan Tastekin, David Hägele, Marina Evers, and Daniel Weiskopf, "Uncertainty-Aware PCA for Arbitrarily Distributed Data Modeled by Gaussian Mixture Models" [Full paper, 2:55pm-3:05pm].

³Timbwaoga A. J. Ouermi, Eric Li, Kenneth Moreland, David Pugmire, Chris R. Johnson, and Tushar M. Athawale, "Efficient Probabilistic Visualization of Local Divergence of 2D Vector Fields with Independent Gaussian Uncertainty" [Short paper, 3:05pm-3:13pm].

⁴Tom Baumgartl, Tatiana von Landesberger, Alessio Arleo, Silvia Miksch, Velitchko Andreev Filipov, Sandhya Rajendran, and Daniel Archambault, "Layers of Doubt: Typology of Temporal Uncertainty in Dynamic Diffusion Networks" [Short paper, 3:13pm-3:21pm].

⁵Frederik L. Dennig and Daniel A Keim, "DE-VAE: Revealing Uncertainty with Variational Autoencoders in Parametric and Inverse Projections using Differential Entropy" [Short paper, 3:21pm-3:29pm].

⁶Jixian Li, Timbwaoga A. J. Ouermi, Mengjiao Han, and Chris R. Johnson, "Uncertainty Tube Visualization of Particle Trajectories" [Full paper, 4pm-4:10pm].

⁷Julius Bañgate, Jacques Gautier, Sidonie Christophe, Déborah Idier, Denis Paradis, and Sophie Lecacheux, "Visualizing uncertainty from meteo-oceanic ensemble data" [Full paper, 4:10pm-4:20pm].

⁸Alp Ö. Yener, Gokturk Ipek, M.D Ali Nural, Okan Akinci, Muhsin Melik, Cevdet Kocogullari, and Selim Balcisoy "Visualizing Diagnostic Uncertainty in Tabular Data: An Information-Theoretic Matrix Approach" [Short paper, 4:20pm-4:28pm].

⁹Cenyang Wu, Qinhan Yu, and Liang Zhou, "Ensemble Visualization With Variational Autoencoder" [Short paper, 4:28pm-4:36pm].

Panelists

Dr. Chaoli Wang, Dr. Alex Kale, and Dr. Menna El-Assady

Dr. Chaoli Wang is a Professor in the Department of Computer Science and Engineering at the University of Notre Dame. He received his Ph.D. in Computer and Information Science from The Ohio State University. Dr. Wang's current research focuses on machine learning and foundation models for data visualization. He has published over 150 peer-reviewed papers in leading international journals and conferences, with his work recognized by multiple Best Paper and Honorable Mention awards from venues such as IEEE VIS, IEEE PacificVis, IEEE CG&A, and VDA. In addition to his research, Dr. Wang has made significant service contributions to the visualization community. He has served as Paper Co-Chair for several major conferences, including IEEE VIS, IEEE PacificVis, IEEE LDAV, ChinaVis, and ISVC. He was previously an Associate Editor of IEEE Transactions on Visualization and Computer Graphics (TVCG). He serves as Chair of the Steering Committee for IEEE LDAV 2025 and International Liaison on the IEEE VGTC Executive Committee.

Dr. Alex Kale is an Assistant Professor in Computer Science and the Data Science Institute at the University of Chicago. He earned his PhD in Information Science at the University of Washington in 2022. Before coming to University of Chicago, Alex held a visiting research position at Northwestern University from 2020 through 2022. He earned a Master’s of Science in Information Science from the University of Washington in 2020 and a Bachelor’s of Science in Psychology, with minors in Music and Philosophy, also from the University of Washington in 2015. Alex leads the Data Cognition Lab at the University of Chicago, focused on creating data visualization and analysis software that explicitly represents users’ cognitive processes around data.

Dr. Menna El-Assady is an Assistant Professor at the Department of Computer Science of ETH Zurich where she leads the Interactive Visualization and Intelligence Augmentation Lab (IVIA). Prior to that, she was a research fellow at the AI Center of ETH Zurich (Switzerland). Before that, she was a research associate and doctoral student in the group for Data Analysis and Visualization at the University of Konstanz (Germany) and in the Visualization for Information Analysis lab at the OntarioTech University (Canada).