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Rethinking data science and generative AI

As part of his dissertation, Janik Wörner showed how data science and generative AI can be used beyond traditional analysis tasks to support decision-making and develop intelligent systems in business and healthcare.

1. the doctorate is complete - what does that mean for you personally?

The successful completion of this milestone fills me personally with pride, as I am aware of how much hard work and perseverance went into it.

2. what is your dissertation about?

As part of my dissertation, I investigated how data science methods and generative AI can be systematically developed and utilised for new domain-specific application potential. The focus was on the question of how data-driven methods can contribute to structured decision support and the design of intelligent digital systems beyond traditional analysis purposes. This addresses economic fields of application such as trend analysis and product development as well as social contexts such as AI-supported assistance and communication systems in the healthcare sector. The work combines methodological developments with application-oriented design approaches to show how data science and generative AI can be used in a context-sensitive, targeted and responsible manner. Overall, the dissertation contributes to the conceptual opening and systematic categorisation of new fields of application for data-driven and generative AI-based systems.

3. what was a highlight or special experience in connection with your doctorate?

A particular highlight of my doctorate was travelling to international conferences to present my scientific work. I particularly remember the conferences in Hyderabad (India) and in Nashville and Florida (USA), as the intensive scientific discourse with smart, internationally networked researchers inspired my own research and provided new impetus in terms of content.

4. what plans do you have for your professional future?

For my professional future, I am initially planning to take the step into practice in order to apply my theoretical knowledge in practice-orientated projects and further expand my horizon of experience. I am interested in working more on concrete challenges and seeing how research ideas (can) unfold their impact in practice. In the long term, however, I can very well imagine returning to the academy - for example as part of a university professorship. I have always particularly enjoyed the exchange with students and the joint work on content-related issues, especially the knowledge transfer and the supervision of student projects.

5. what tips can you give future doctoral candidates?

First and foremost: persevere! And don't lose the fun in the process.

6th Why did you choose OTH Regensburg for your doctorate?

Because of the OTH's excellent reputation and its proximity to the University of Regensburg.

Photo: Julia Wagner

Janik Wörner (Karlsruhe, 1994)

Profile

    • Subject

      Business Informatics

    • PhD subject

      Dr. rer. pol.

    • PhD period

      2020 -2025

    • Faculty

      Economics

Subject

PhD subject

PhD period

Faculty

Business Informatics

Dr. rer. pol.

2020 -2025

Economics

    • Supervisors

      Prof. Dr. Susanne Leist, University of Regensburg, Vice President for Digitalisation, Networks and Transfer at the University of Regensburg, Prof. Dr. Gregor Zellner, OTH Regensburg

    • Title of the dissertation

      Automated exploitation of the knowledge potential of digital data - conception and development of intelligent analysis methods and tools for the operationalisation of user-generated data using data science and generative artificial intelligence

Supervisors

Title of the dissertation

Prof. Dr. Susanne Leist, University of Regensburg, Vice President for Digitalisation, Networks and Transfer at the University of Regensburg, Prof. Dr. Gregor Zellner, OTH Regensburg

Automated exploitation of the knowledge potential of digital data - conception and development of intelligent analysis methods and tools for the operationalisation of user-generated data using data science and generative artificial intelligence