14+ successfully supervised bachelor and master theses
Biographie
Visual analytics, human-AI interaction, and applied data science.
I am an academic researcher at TU Wien, where I am part of the CVAST lab and employed in the Bilateral AI Cluster. My research focuses on visual analytics and human-AI interaction, with interests in heterogeneous data, network analysis, geographical data science, the digital humanities, and explainable AI.
Before joining TU Wien, I was part of the DBVIS group at the University of Konstanz. My former industry and applied data science experience includes work with Vidatics GmbH, work for DER SPIEGEL, and active participation in CorrelAid X Konstanz.
Teaching
I contributed to visualization, visual analytics, data mining, and applied data science teaching across several semesters.
Data Visualization Basic Concepts
Data Visualization Advanced Topics
Data Visualization Basic Concepts
Applied Visual Analytics
Applied Visual Analytics
Data Visualization Advanced Topics
Data Visualization Basic Concepts
Applied Visual Analytics
Applied Visual Analytics
Data Mining Basic Concepts
Data Visualization Basic Concepts
Research Projects & Proposals
I have contributed to 5+ active research proposal, project writing, and execution processes, especially around visual analytics, explainable AI, and human-AI collaboration.
Selected projects and proposals I contributed to include:
CUEPAQ
Visual analytics and linguistics project on capturing, understanding, and explaining personalized argument quality. My work connects argument data, projections, and interactive explanation for richer analysis of argumentative structures.
Bilateral AI Cluster
FWF Cluster of Excellence combining symbolic and sub-symbolic AI toward broader, more explainable AI systems. My role is situated at the visual analytics interface: making AI behavior, data curation, and model explanations inspectable.
SFB-TRR 161
Collaborative research center on quantitative methods for visual computing, with research areas spanning models, measures, adaptive algorithms, interaction, and applications. This shaped my work on evaluating and explaining visual analytic methods.
SINOISI
CVAST project context around visual analytics and sensemaking for complex information spaces. I connect this line of work to interactive exploration, human-AI collaboration, and explanation-centered interfaces.
Challenges & Community
Graph Drawing Contest
I enjoy taking part in challenge formats because they sharpen problem framing, visual reasoning, and fast prototyping around graph and network visualization tasks.
VAST Challenge
VAST-style challenge settings are a useful testbed for sensemaking under uncertainty: complex data, suspicious-pattern analysis, and visual analytics workflows under time pressure.
ARC-AGI Challenge
I am currently participating in the ARC-AGI challenge, exploring abstract reasoning, agentic interaction, and how systems can infer rules from sparse examples.
Supervisors
- Silvia Miksch Head of CVAST and Professor for Visual Analytics at TU Wien.
- Elisabeth Lex Full Professor at Graz University of Technology, working on recommender systems, information retrieval, and data science.
- Daniel A. Keim Professor of Computer Science and chairholder of the DBVIS group at the University of Konstanz.