Katerina Vrotsou

Associate Professor, Docent

Publications

2026

Peilin Yu, Aida Nordman, Takanori Fujiwara, Marta Koc-Januchta, Konrad Schönborn, Lonni Besançon, Katerina Vrotsou (2026) IEEE Transactions on Visualization and Computer Graphics, Vol. 32, p. 1142-1152 (Article in journal)

Maria Eidenskog, Wiktoria Glad, Saghi Hajisharif, Fatemeh Johari, Katerina Vrotsou (2026) Proceedings of the 59th Hawaii International Conference on System Sciences, p. 5541-5548 (Conference paper)

Nico Reski, Carlo Navarra, Lotten Wiréhn, Tina-Simone Neset, Aris Alissandrakis, Aitor Aldama Campino, Fuxing Wang, Isabel Ribeiro, Jorge H. Amorim, Andreas Kerren, Katerina Vrotsou (2026) Virtual Reality, Vol. 30, Article 7 (Article in journal)

Francesca Zerbato, Lisa Zimmermann, Katerina Vrotsou, Barbara Weber (2026) Information Systems, Vol. 135, Article 102596 (Article in journal)

2025

Elmira Zohrevandi, Aida Nordman, Anders Ynnerman, Jonas Lundberg, Carl Westin, Katerina Vrotsou (2025) 2025 IEEE Conference on Engaging Critical Workforce In co-Design aNd Assessment (ECWIDNA), p. 29-33 (Conference paper)

Research

Inside Wadstr枚ms Exploranation Laboratory

Media and Information Technology

Develops edge competence in visual AI, visualization, graphics and human-centered tech with strong human-in-the-loop focus. Combines research excellence with national and international collaboration for societal impact.

Climate research presented in the Norrk枚ping Decision Arena

Exploring the transformative potential of climate services

The project explores how next-generation climate services can support societal transformation through data, visualisation and communication 鈥� with a focus on energy, agriculture and urban planning.

Information Visualization

The group focuses on the explorative analysis and visualization of typically large and complex information spaces. We develop novel interactive visualization methods and tools that are able to efficiently support analysts from various domains.

Exploring the potential of generative AI based data synthesis for the future energy system: data, models, biases and implications

This project explores how synthetic data can improve the understanding and forecasting of energy use from different perspectives, to contribute to a more sustainable, resilient, and inclusive housing for the future.

Organisation

People watching a show in a dome theatre

Media and Information Technology (MIT)

At the division of Media and Information Technology we do exciting and well-known research and teaching at undergraduate as well as graduate levels.

Department of Science and Technology (ITN)

We research and teach in several technical and scientific disciplines in which our main areas are organic electronics, media, communications and logistics.

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