Lena Cibulski

My research activities center around the design of visualization tools that assist people in making data-informed decisions. I study how visualizations can amplify the often intangible, experiential knowledge underlying human reasoning with data and how this can benefit from computational support.

Interests
  • Multivariate/Temporal Data Visualization
  • Application-Driven Research
  • Analytics and Decisions
  • Human Factors and Cognition
Education
  • PhD in Visualization, 2024

    Technical University of Darmstadt, Germany

  • MSc in Computer Science, 2017

    Otto-von-Guericke University Magdeburg, Germany

  • BSc in Visual Computing, 2016

    Otto-von-Guericke University Magdeburg, Germany

January 27, 2026

I am honored to win the 1st prize in the Fraunhofer ICT Dissertation Award 2025!

November 5, 2025

Best Short Paper Honorable Mention at IEEE VIS! I also contributed as a panelist and session chair!

My Research

My research blends methodologies from computer science, design, and decision theory to address challenges that arise in a variety of application areas such as engineering or life sciences. These include decision-making under conflicting objectives, parameter space exploration, domain knowledge exploitation, feature engineering for computational support, or analysis of cause-effect relationships. I am also interested in how reflections on the practice of crafting visualizations for real-world problems inform the refinement of methods for visualization research.

If you would like to work with me, please reach out! I am particularly interested in multidisciplinary discussions on human factors, methodological aspects of visualization research, and real-world applications.

Featured Publications
Recent Publications
Visual Analysis of Time-Dependent Observables in Cell Signaling Simulations

Visual Analysis of Time-Dependent Observables in Cell Signaling Simulations

Proceedings of the Eurographics Workshop on Visual Computing for Biology and Medicine - Short Papers, 2025

Best Short Paper Award EG VCBM 2025

Towards Understanding Decision Problems as a Goal of Visualization Design

Towards Understanding Decision Problems as a Goal of Visualization Design

Proceedings of the IEEE Visualization Conference - Short Papers, 2025

Best Short Paper Honorable Mention IEEE VIS 2025

Visualization Building Blocks and Scenarios: A Card-Game Based Learning Framework for the InfoVis Design Space

Visualization Building Blocks and Scenarios: A Card-Game Based Learning Framework for the InfoVis Design Space

Proceedings of the IEEE Visualization Conference - Posters, to be published, 2025

Visual Analysis for Multi-Attribute Choice

Visual Analysis for Multi-Attribute Choice

Dissertation, 2024

1st prize in Fraunhofer ICT Dissertation Award 2025

Best Dissertation in Computer Science at TU Darmstadt in 2024

VRVis Visual Computing Award Honorable Mention 2025

A User-Centered Perspective on Information Needs of Stakeholders in the Circular Economy

A User-Centered Perspective on Information Needs of Stakeholders in the Circular Economy

Proceedings of the Electronics Goes Green 2024+, 2024

Invited Talks
Teaching

I engage in teaching with an integrated master course on recent advances in visualization research and its applications as well as exercise sessions for master courses on visualization, visual analytics, and data science. I also give guest lectures on selected visualization topics from time to time.

Courses
Master Theses

On-Going

  • B. Köse - User Interfaces for Preference Elicitation
  • F. Gärtner - Interactive Cluster Manipulation for Temporal Parallel Coordinates Axes
  • M. Brüggemann - Visual Analysis of Microbiome Data Using Topic Modeling

Former Students

  • P. Roether-Heß - Entwicklung und Visualisierung KI-basierter Entscheidungsunterstützung für die Differenzialdiagnostik von Demenzerkrankungen
  • M. Langer (TU Darmstadt) - Nutzerorientierte Entwicklung einer Visualisierung für Messdaten aus der Fahrzeugerprobung
  • T. Reiner (TU Darmstadt) - Visual Inference for Modeling and Reasoning With Bayesian Networks
  • S. Hainzl (TU Darmstadt) - Bridging the Domain Gap: Visual Identification of Domain-Invariant Features in Time Series
  • M. Nieslony (TU Darmstadt) - Visuelle Analyse des Antriebsdegradationsverhaltens von PHEV- und BEV-Fahrzeugen im Kontext der Dauerlauferprobung
  • H. Pfeifer (TU Darmstadt) - A Visual Analytics Approach to Sensor Analysis for End-of-Line Testing