Research Interests

My research focuses on the intersection of graph drawing and network visualization as well as set visualization. Networks accompany us in our daily life, for example, social networks, transport networks, or biological networks, and therefore it is important to better understand them. Network visualization can help us handle the increasing complexity of modern datasets we are facing. My background in graph drawing allows me to understand and develop computationally efficient algorithms. Still, computational experiments only tell one side of a story and I think that evaluation with real users is an important aspect of my research. 

More specifically, I have worked on edge bundling, a clutter reduction technique to enhance patterns present in a network, and metaphorical set visualization. For both topics I have developed novel algorithms and evaluated them in controlled user experiments. I am always looking for new topics and potential collaboration in this area.   

Short CV

2024-today	Post-Doc Technical University of Munich Chair for Efficient Algorithms (Prof. Stephen Kobourov)
2016-2020	Dr. rer. tech. TU Wien • Topic: Exploring Graph-based Concepts for Balanced Information Density in Data Visualizations Advisor: Martin Nöllenburg
2014-2016	M.Sc. in Visual Computing TU Wien • Thesis Topic: Metro Map Metaphor for Set Visualization Advisors: Martin Nöllenburg
2010-2014	B.Sc. in Computer science University of Innsbruck
2010	Matura Höhere Technische Lehranstalt Saalfelden

Publications

Please refer to the list on DBLP.

Awards

• Award of Excellence BMBWF (Award for best dissertations by the Austrian Education Ministry)
• Best Poster Award at GD 2023
• Best Paper Award at PacificVis 2023
• Distinguished Young Alumni Award – Nominee TU Wien (Award for best Master Thesis in Computer Science)
• Best Poster Award at GD 2020
• Second Place at GD Contest 2019 Creative Contest
• Second Place at GD Contest 2018 Creative Contest 

Teaching

• Introduction to Information Visualization (Bachelor) SS25
• Information Visualization (Master) WS24/25
• Practical Course on Algorithm Design for Competitive Challenges WS24/25
• Algorithms and Datastructures SS21, SS22, SS23