Interdisciplinary Data Science Conference
Interdisciplinary Data Science Conference

Keynote Speakers

2J3A2497

Viola Gallina
Senior Researcher - Fraunhofer Austria

Title: "Digital Product Passport Standardization in a European and Global Context"

Abstract

This keynote offers a strategic overview for industry leaders, policymakers, and innovators seeking to navigate the rapidly evolving landscape of Digital Product Passports (DPPs). This talk will cover:

  • The current state of DPP-system standardization efforts led by CEN, CENELEC, and ETSI, and how they align with broader initiatives such as the United Nations Traceability Protocol (UNTP), and GS1 standards.
  • The key challenges around DPP-data, including issues of data comparability (e.g. CO₂ footprint, repairability scores), interoperability, and the role of ontologies and knowledge graphs in enabling seamless, machine-readable information exchange across sectors.
  • How the convergence of regulatory pressure and technological innovation is creating both a challenge and an opportunity for European and global actors alike.

This keynote isn’t just about compliance—it’s about preparing your organization to thrive in a digital, transparent, and circular economy. Learn how to position your company at the forefront of sustainability-driven innovation, and be part of shaping the standards that will define the next generation of smart, traceable, and verifiable products.

Profile

Dr. Viola Gallina is a senior researcher in the Factory Planning and Production Management division at Fraunhofer Austria. Her previous research focused on mathematical programming and machine learning. Currently, her work centers on the circular economy, with a particular emphasis on its data-driven aspects. Her main area of focus is the digital product passport. She earned her PhD and MBA from TU Budapest and teaches at TU Vienna.

Ruben Hetfleisch
Lead Generative AI Community - AI Austria / Founder - Klartext AI / Research Associate - Fraunhofer Austria

Tentative Title: "State of Generative AI - Where are we and where do we want to go?"

Abstract

Generative AI has rapidly advanced from research labs into mainstream use, transforming how we create content, design systems, and interact with machines. In Austria and across Europe, we are witnessing promising innovation in sectors such as healthcare, manufacturing, and the creative industries. However, we face critical challenges: from limited access to foundational models and computing infrastructure to the need for robust regulatory frameworks that balance innovation with trust and safety and dont just confuse. This keynote explores the current capabilities of generative AI, highlights Europe's unique strengths—such as its focus on interdisciplinary research—and outlines what must change to ensure Europe doesn't just keep up, but leads globally in the next phase of AI development.

Profile

Ruben Hetfleisch researches at Fraunhofer Austria on generative AI with a focus on the trustworthiness of language models. While being involved in projects ranging from the automation of sustainability reporting to the creation of the first austrian legal LLM, he runs an AI startup that uses generative AI to make complex documents accessible and easy to understand. He also is the founder of the first GenAI-specialized platform in Austria called “GenAI Community by AI Austria”, where his goal is to further push the GenAI ecosystem.

Ruben Hetfleisch
Hilda Kosorus

Hilda Kosorus
Founder & IT Strategist - Onefold.ai

Title: "Agentic AI: Unleashing the Next Wave of Transformation"

Agentic AI represents a groundbreaking technological shift poised to transform business operations in 2025 and beyond.  Imagine AI systems that think, decide, and solve complex problems autonomously, dramatically boosting productivity and reshaping competitive landscapes.

Abstract

This talk is an essential guide for decision-makers and tech leaders to harnessing this technology.
Discover:

  • How Agentic AI will revolutionize industries
  • Practical strategies to implement and leverage AI agents
  • Ways to future-proof your organization and stay ahead of the curve
  • Ethical considerations and best practices for responsible AI adoption

Don't risk being left behind in the AI revolution. Join us to unlock the secrets of Agentic AI and position your business at the forefront of innovation. This isn't just about understanding a new technology—it's about seizing a competitive advantage that will define the next era of business success.
Prepare to lead, not follow, in the age of Agentic AI.

Profile

Founder of Onefold.ai, an AI consultancy dedicated to simplifying AI adoption for businesses. With a Ph.D. in Computer Science and over 15 years of experience in AI and machine learning, I specialize in translating complex AI concepts into actionable strategies. At Onefold.ai, we guide companies from initial blueprints to full-cycle implementations, ensuring AI is accessible and delivers measurable ROI. Our mission is to unlock business potential through a straightforward, no-nonsense approach that drives real-world results and empowers organizations to harness the power of AI effectively.

Simon Hirländer
Team Lead Reinforcement Learning and Smart Analytics - University of Salzburg - IDA Lab

Tentative Title: "From Theory to Practice: Reinforcement Learning as the 21st-Century ML Paradigm"

Abstract

Reinforcement Learning is reshaping the very notion of machine intelligence, transforming rigorous theoretical constructs into impactful real-world capabilities. Beyond solving specific tasks, Reinforcement Learning is overcoming long-standing formal limitations in decision-making and reasoning, opening a credible path toward true artificial intelligence. The recent awarding of the 2025 Turing Prize to Richard S. Sutton and Andrew G. Barto stands as a testament to the central role Reinforcement Learning now plays in the evolution of machine learning.

In only a few years, Reinforcement Learning has transcended reactive behavior. It now empowers agents to reason through learned models of the world, to predict, to plan, and to adapt dynamically in complex and uncertain environments. Breakthroughs in model-based control, safe exploration strategies, large-scale multi-agent coordination, and integrated reasoning architectures have accelerated both the scientific frontier and the technological transformation of the digital world.
Today, Reinforcement Learning is no longer confined to laboratories or isolated applications. It is emerging as the computational foundation for intelligent and adaptive systems across science, industry, and society.
Looking forward, Reinforcement Learning will become an invisible infrastructure woven into the fabric of everyday life. It will orchestrate interactions among humans and machines, propel scientific discovery, and enable new forms of collective intelligence that will define the next era of technological progress.

Profile

Dr. Simon Hirländer leads the “Smart Analytics & Reinforcement Learning” team at the IDA Lab of Paris Lodron University Salzburg (PLUS). Following several years of international research at CERN—where he also obtained his PhD—he focused on optimizing complex systems such as the CERN accelerator complex using machine learning, particularly reinforcement learning (RL). In addition, he explores a broad range of RL applications in fields like robotics, telecommunications, and quantum computing. Beyond his research, Dr. Hirländer works closely with local industry partners in Salzburg to implement advanced analytics methods such as anomaly detection, time series analysis, and automated classification processes. He is also actively involved in providing professional training for these partners and lectures at the university on topics including reinforcement learning and data analytics. Together with his team, he strives to translate the latest scientific insights into practical solutions for businesses and industry, and organises international events such as the first international RL Bootcamp, held in Salzburg last year.

Simon Hirländer
CarinaSeidel

Carina Seidel
Head of Data Science & Analytics - Runtastic GmbH

"Best Practises in Advanced Analytics / Real Life Examples and Use Cases of Data Science Modells"

Abstract

How we worked and why did it work?

We had a centralized Data Team collaborating with departments at Runtastic. This team was set up with Data Engineers, Data Analyst, Data Scientist and Machine Learning Engineers. A team of experts is a good start, in this speech I will tell you how we collaborate and how we embed ourselves in the organisation.

Use Case - Question why and especially how?

In this current age AI is a hype and everyone has seen that it can help us and make our lives easier. But implementing a Use Case in a business organisation still brings challenges. So how did we approach it at Runtastic? In this talk I will elaborate how we implemented a Data Science Model to bring value for the Runtastic Organisation.

Profile

Carina Seidel is the Head of Data Science & Analytics at Runtastic GmbH, where she leads a team dedicated to leveraging data to enhance user experiences and drive business growth. With extensive experience in data analysis, visualization, and business intelligence, Carina has a proven track record of implementing data-driven strategies to optimize performance and innovation. Her expertise spans various domains, including online marketing and technical leadership.

Stefan Zeppetzauer
Vice President Integrated Diagnostics and Aftersales Transformation / Software Defined Vehicles - KPIT Technologies GmbH

Tentative Title: "Data-Driven Revolution in Software Defined Vehicles: From Insights to Decision-Making"

Abstract

The presentation discusses the applications of data analytics and AI in automotive software. It highlights the challenges of working with large trace files, including scalability, data quality, and complexity. The presentation also explores the use of cloud capabilities to optimize analytical capabilities and automation. Leveraging AI and ML capabilities can help query trace files for correlations of signals, errors, and root causes. Additionally, the presentation touches on the concept of software-defined vehicles and the after-sales process. It mentions the importance of predictive maintenance, driver behavior, and user management in the vehicle lifecycle management. The use of digital twin infrastructure services and data platforms is also discussed. The presentation aims to improve the turnaround time and efficiency of automotive software development. It emphasizes the need for access, view, and edit data via chatbots and the implementation of agentic AI to automate process flows. The applications of data analytics and AI in automotive software have the potential to revolutionize the industry. Overall, the presentation provides an overview of the current trends and challenges in the field of automotive software development, highlighting the potential of data analytics and AI to drive innovation and improvement.

Profile

Highly experienced technology professional with a strong background in computer science and telecommunication & -systems. Born in Salzburg, Austria, I graduated in 2005 with a MSc degree from Halmstad University in Sweden and at the University of Applied Science in Salzburg. My career has spanned over two decades, with early beginnings as a Software Developer at In2Soft GmbH. I joined KPIT Technologies GmbH in 2010, taking on key roles in customer projects and eventually leading the Diagnostic Business Unit globally since 2015. Currently, I oversee both the Diagnostic Business Unit (called iDART) and the Software Products of Technical Engineering in the Automotive SDV segment.

Stefan Zeppetzauer2