In our ever-more digital world, science faces one great challenge: to build trust in artificial intelligence, machine learning, cyber security and similar disciplines. The Research Center Trustworthy Data Science and Security tackles this challenge at the intersection between technological progress and social acceptance. We focus on the trustworthiness of intelligent systems in safety-critical applications. A unique, human-centered approach encompasses all the interdisciplinary research in trustworthy data analytics, explainable machine learning and privacy-aware algorithms. Our goal: to develop trustworthy intelligent systems and enable private citizens to understand that technology.



Portrait of Emmanuel Müller Photo: TU Dortmund

»We need fundamental research on "Calibrated Trust". Machine learning should be equally perceived as trustworthy by humans but also ensure the necessary technical reliability. A balance between both is important for a sustainable, trustworthy AI!«

Prof. Dr. Emmanuel Müller, TU Dortmund University

Our Research

We envision a unique interdisciplinary research approach that covers the entire spectrum of research challenges in all facets of trustworthy and privacy-aware technologies. We seek to answer long-term research questions such as: What can be done to help people understand intelligent systems? How can we incorporate provable trust and security guarantees in machine learning processes? And how do we balance privacy and functionality? Meaningful progress in these areas requires close collaboration among a variety of disciplines. Our research center does this by building upon the University Alliance Ruhr’s strengths – from psychology to data science.

Mission Statement

Job offers

Join our team! We are looking to recruit researchers at all levels to strengthen and augment our interdisciplinary team. We want to conduct fundamental theoretical research and investigate practical applications in interdisciplinary projects. Our researchers work in a creative and attractive world-class research environment that encourages them to harness and build networks among our students, postdocs and professors. You can work on research projects that span computer science, statistics and psychology to tackle and foster next-generation research on trust.

Work with us!



Into life

Many data-driven sciences require robust methods of data analysis, as the majority of data can no longer be examined by human experts alone. As automation increases, so do the standards that autonomous systems have to meet to be trusted in fields such as medicine or life sciences. Partners from industry and society can benefit from our innovative teaching approach aimed at practical and interdisciplinary education. For example, regular citizen science events and industry discussion forums will be held at least twice a year to enable scientists to learn more about the needs of different sectors (e.g., industry, local government and administration, health care). These offerings should also help to communicate scientific findings to society and discuss them with the public.

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