Publications

Guillermo Pérez-Hernández, und Peter W. Hildebrand. mdciao: Accessible Analysis and Visualization of Molecular Dynamics Simulation Data. PLOS Computational Biology, (21)4:1-17, Public Library of Science, April 2025. [PUMA: molecular_dynamics visualization yaff] URL

Christina Gillmann, Johanna Schmidt, und Daniel Wiegreffe. Visualization in the Wild. IEEE Comput. Graph. Appl., (43)6:46--49, Institute of Electrical and Electronics Engineers (IEEE), November 2023. [PUMA: Visualization xack]

Jeremias Schebera, Dirk Zeckzer, und Daniel Wiegreffe. A layout framework for genome-wide multiple sequence alignment graphs. Frontiers in Bioinformatics, (4)Frontiers Media SA, August 2024. [PUMA: genome_analysis genome_comparison graph_drawing multiple_sequence_alignment visualization xack] URL

Weizhou Luo, Zhongyuan Yu, Rufat Rzayev, Marc Satkowski, Stefan Gumhold, Matthew McGinity, und Raimund Dachselt. PEARL: Physical Environment based Augmented Reality Lenses for In-Situ Human Movement Analysis. CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 19.04.2023. [PUMA: Analytics, FIS_scads Immersive In-situ affordance, analysis, augmented/mixed data movement physical reality, referents, topic_visualcomputing visualization xack]

Aryaman Gupta, Ulrik Günther, Pietro Incardona, Guido Reina, Steffen Frey, Stefan Gumhold, und Ivo F. Sbalzarini. Efficient Raycasting of View-Dependent Piecewise Constant Representations of Volumetric Data. 17.06.2022. [PUMA: FIS_scads Human-centered Visualization Visualization, and computing, concepts paradigms, techniques theory, topic_lifescience topic_visualcomputing xack]

Patrick Ebel, Kim Julian Gülle, Christoph Lingenfelder, und Andreas Vogelsang. ICEBOAT: An Interactive User Behavior Analysis Tool for Automotive User Interfaces. Adjunct Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology, Association for Computing Machinery, New York, NY, USA, 2022. [PUMA: Design Driving Human-Computer In-Vehicle Information Interaction Naturalistic System Tools Visualization topic_visualcomputing zno data] URL

Marzan Tasnim Oyshi, Verena Maleska, Jochen Schanze, Franziskus Bormann, Raimund Dachselt, und Stefan Gumhold. FloodVis: Visualization of Climate Ensemble Flood Projections in Virtual Reality.. EnvirVis@ EuroVis, 1--9, 2022. [PUMA: Climate Ensemble Flood FloodVis Projections Reality. Virtual Visualization topic_visualcomputing yaff xack]

Britta Pester, Benjamin Russig, Oliver Winke, Carolin Ligges, Raimund Dachselt, und Stefan Gumhold. Understanding multi-modal brain network data: An immersive 3D visualization approach. Comput. Graph., (106)C:88–97, Pergamon Press, Inc., USA, August 2022. [PUMA: EEG Immersive Origin–destination Partial brain coherence connectivity directed reality topic_visualcomputing virtual visualization zno] URL

Timo P. Gros, David Groß, Stefan Gumhold, Jörg Hoffmann, Michaela Klauck, und Marcel Steinmetz. TraceVis: Towards Visualization for Deep Statistical Model Checking. Leveraging Applications of Formal Methods, Verification and Validation: Tools and Trends: 9th International Symposium on Leveraging Applications of Formal Methods, ISoLA 2020, Rhodes, Greece, October 20–30, 2020, Proceedings, Part IV, 27–46, Springer-Verlag, Berlin, Heidelberg, 2020. [PUMA: Checking Model Statistical Visualization nopdf networks neural] URL

Jan Tiemann, Matthew McGinity, Ivo F. Sbalzarini, und Ulrik Günther. Live and Interactive 3D Photomanipulation under the Microscope using Virtual Reality. Extended Abstracts of the 2024 CHI Conference on Human Factors in Computing Systems, Association for Computing Machinery, New York, NY, USA, 2024. [PUMA: control, human-computer interaction, microscope reality, topic_lifescience virtual visualization zno] URL

Ulrich von Zadow, und Raimund Dachselt. GIAnT: Visualizing Group Interaction at Large Wall Displays. Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 2639–2647, Association for Computing Machinery, New York, NY, USA, 2017. [PUMA: analysis, awareness, collaborative coupling, multitouch, navigation, physical territoriality, visual visualization work, zno] URL

Akshay Akshay, Mitali Katoch, Navid Shekarchizadeh, Masoud Abedi, Ankush Sharma, Fiona C Burkhard, Rosalyn M Adam, Katia Monastyrskaya, und Ali Hashemi Gheinani. Machine Learning Made Easy (MLme): a comprehensive toolkit for machine learning-driven data analysis. Gigascience, (13)Januar 2024. [PUMA: AutoML analysis classification data learning machine problems topic_federatedlearn visualization xack yaff]