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

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