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

May 27, 2025

I am proud to be awarded for the best dissertation in Computer Science at TU Darmstadt in 2024!

Jan 30, 2025

I am honored to receive an Honorable Mention at the VRVis Visual Computing Award 2025!

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

Visual Analysis for Multi-Attribute Choice

Lena Cibulski

This dissertation presents findings from problem-driven research that centers around the design of visualization tools to assist experts in making data-informed choices. Its theoretical, methodological, and technical contributions shape the understanding of decision-related activities on large data sets and how to support them with visualization.

Aug 2024

Revisiting PAVED: Studying Tool Adoption After Four Years

Lena Cibulski, Thorsten May

We revisit the adoption of PAVED in the target domain after four years. Our survey reveals a small number of power-users and helps carve out factors that influence whether and how a tool is adopted in the intended work environment.

May 2024

PAVED: Pareto Front Visualization for Engineering Design

Lena Cibulski, Hubert Mitterhofer, Thorsten May, Jörn Kohlhammer

We present a design study on Pareto front visualization to support engineers in applying their expertise and subjective preferences for selection of the most-preferred electric motor design. We propose PAVED, an interactive parallel coordinates visualization for exploration of multi-criteria alternatives.

Jul 2020

Recent Publications