Data Science + AI Day 2026 „Advancing Artificial Intelligence We Can Trust and Understand"
Dachsaal, Urania Wien | 22. Juni 2026 | 10:30–20:00
Uraniastraße 1, 1010 Wien
Recent advances in AI are reshaping almost every corner of science and society. Steering these advances in a positive direction will require close collaboration across many academic disciplines, institutions, industry, and the broader public. On June 22, the Data Science Network invites the entire campus to explore the breadth and depth of theoretical and applied AI contributions across Vienna's universities with two panels and keynotes showcasing how researchers across our departments are advancing interpretable AI systems we can trust and understand.
You may register for the morning programme, the afternoon programme, or the full day including lunch catering.
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Registration
Program and Schedule
10:30 – DS Day Welcome Remarks
Univ.-Prof. Dr. Claudia Plant
University of Vienna, Research Group Data Mining and Machine Learning
Head, Data Science Network
10:45–11:00 – iLab: Venture Creation Opportunities
Marco Masia, PhD MBA
University of Vienna, Research Services and Career Development
Head of Entrepreneurship
11:00–11:15 – uniport Presentation
Joyce Fasan, M.A.
University of Vienna, Uniport – Karriereservice Universität Wien GmbH
Project & Event Manager
11:30–12:00 – Data Science Poster Session
Presentations by Master students of Data Science, Business Analytics, and Digital Humanities.
12:00–13:00 – Lunch Break and Poster Exhibition
13:15 – AI Day Welcome
Univ.-Prof. Dr. Claudia Plant
University of Vienna, Research Group Data Mining and Machine Learning
Head, Data Science Network
Univ.-Prof. Dr. Krzysztof Janowicz
University of Vienna, Spatial Data Science & GeoAI
Program Chair, Data Science + AI Day 2026
Executive Board Member, Data Science Network
13:30 – Welcome Speech
Univ.-Prof. Dr. Manuela Baccarini
Vice Rector for Research and International Affairs
University of Vienna
14:00–14:45 – Neurosymbolic Keynote
“A Polanyian Neurosymbolic Cognitive Architecture”
Prof. Aldo Gangemi
Full Professor, Department of Philosophy
University of Bologna
Semantic Technologies, Artificial Intelligence, and Cognitive Science
Abstract
Michael Polanyi’s well-known observation that “we can know more than we can tell” (Polanyi, 1966) captures a central challenge for knowledge-based systems: how can we represent the vast amount of tacit knowledge that underlies human sense-making, including presuppositions, causality, perspectives, theory of mind, ethical considerations, and motor or kinematic patterns?
POLANYI++ is a neurosymbolic cognitive architecture designed to address this challenge by integrating four research traditions:
- Cognitive neuroscience, providing the computational substrate (Bind–Reify–Integrate, BRI), inspired by neural binding (Fries, 2015) and free-energy minimization (Friston, 2010);
- Formal ontology, providing logical (OWL2), representational (grounded world models), and design (Ontology Design Patterns) components;
- LLM context engineering as an abductive reasoning engine; and
- Knowledge engineering plug-and-play components (Newell, 1982; Clancey, 1985; Wielinga et al., 1992; Motta, 1999).
Multimodal large language models are used as tacit knowledge simulators and are orchestrated through a formally specified instruction set while preserving the separation between domain knowledge, task models, and problem-solving methods. The architecture is independent of any specific agentic runtime and can serve as a blueprint for a variety of implementations.
14:45–15:45 – Neurosymbolic Panel
“Neurosymbolic AI: Towards Interpretable Intelligence”
Chair: Univ.-Prof. Dr. Claudia Plant
Panelists
- Univ.-Prof. Dr.-Ing. Moritz Grosse-Wentrup
Research Group Neuroinformatics, University of Vienna - Asst. Prof. Dr. Fajar J. Ekaputra
Institute for Data, Process & Knowledge Management, WU Vienna - Asst. Prof. Dr. Julia Neidhardt
Research Unit Data Science, TU Wien Informatics - Ass.-Prof. Sebastian Schuster, MSc, PhD
Research Group Data Mining and Machine Learning, University of Vienna - Assoc. Prof. Dr. Sebastian Tschiatschek
Research Group Data Mining and Machine Learning, University of Vienna
15:45–16:15 – Coffee Break
16:15–17:00 – Ethics Keynote
“The Urgent Challenge of Technology-Facilitated Gender-Based Violence”
Prof. Miriam Fernandez
Professor of Responsible Artificial Intelligence
Knowledge Media Institute (KMi)
The Open University, United Kingdom
Abstract
While online spaces have become central to social interaction, they remain profoundly unsafe for many. Women and girls, in particular, continue to face disproportionate risks from technology-facilitated violence, including harassment, stalking, deepfake pornography, and algorithmic discrimination.
This talk explores how current technologies and online environments perpetuate and amplify gender-based harms. It highlights ongoing initiatives and research efforts aimed at addressing these issues, while also discussing the technical, social, and legal challenges that continue to hinder meaningful protection for women and girls worldwide.
17:00–18:00 – Ethics Panel
“Ethical Agents: Autonomy Meets Responsibility”
Chair: Univ.-Prof. Dr. Krzysztof Janowicz
Panelists
- Asst. Prof. Dr. Martin Pawelczyk
Research Group Data Mining and Machine Learning, University of Vienna - Asst. Prof. Dr. Tabea Ott
Department of Systematic Theology and the Study of Religions
Department for Ethics and Law in Medicine
University of Vienna - Assoc. Prof. Dr. Dagmar Gromann
Computational Linguistics & NLP
Centre for Translation Studies
University of Vienna - Rodrigo Conde-Jimenez, Phd Researcher
AI Ethics Lab, Center for Innovation Systems and Policy
Austrian Institute of Technology
18:00 – Poster Award Ceremony
18:30–20:00 – Closing Reception
Networking, finger food, and drinks.