Research Focus Digital Living Environments and Health

Medical Informatics within the Digital Living Environments and Health research focus at Heilbronn University of Applied Sciences is dedicated to the scientific development and technical design of medical information processing. It addresses the question of how complex health data can be structured, standardized, and represented in digital systems so that they can be reliably used for care, documentation, and research.

HHN's expertise lies in the development of interoperable information systems, analysis and design of information-supported processes, development of specialized software solutions, and the use of computer simulation models to examine and optimize complex systems in healthcare. The GECKO Institute and the MOLIT Institute, an affiliated institute of HHN, play central roles in this endeavor. While the GECKO Institute brings together these approaches in application-oriented research contexts, validates them under real conditions, and supports their transfer into sustainable digital care structures, the MOLIT Institute focuses on model-based information logistics in healthcare and brings its expertise in optimizing clinical processes, resource planning, and data-driven decision support. Together, both institutes form a powerful bridge between theoretical research and practical implementation of digital health solutions.

This research- and application-oriented competence base also forms a solid foundation for scientific education in the field of medical informatics. For more than 50 years, in close cooperation with the University of Heidelberg, the joint study program Medical Informatics has created an interdisciplinary environment that offers excellent prospects for research, innovation, and young scientists in the field of tension between medicine, informatics, and an increasingly digitized society.

Public Health and Health Management use evidence-based data to connect individual health trajectories with overarching care and system issues. The focus is on generating new evidence from personalized health and context data and feeding it back into individualized decision-making and intervention processes. Health data thus serves not only to describe populations, but forms the basis for dynamic, context-dependent models in prevention, care, and management.

HHN focuses on the integration of heterogeneous data sources and their use for evidence-based decisions to further develop care structures and health governance. Additionally, the GECKO Institute evaluates data-driven and digital innovations from a health economics and health services research perspective, particularly with regard to efficiency, quality, and system impact.

This research area thus functions as an interface between individual health dynamics and systemic control, where data-based decision models contribute to the development of adaptive and learning health systems.

The forward-looking research area Artificial Intelligence and Data Science combines methodological excellence in machine learning, deep learning, and statistical modeling with concrete application fields such as production, mobility, health, and sustainability. Reproducibility, empirical validation, and data-ethical assessment are the central guiding principles.
HHN offers specialized degree programs, such as the Bachelor's Applied Artificial Intelligence and the Master's Applied Artificial Intelligence.

The Interdisciplinary Center for Machine Learning is HHN's cross-faculty competence center, which provides state-of-the-art hands-on teaching with its physical and virtual AI laboratory demonstrators, AI office hours, workshops, and continuing education programs, thus promoting the transfer of research results to the region. A particular focus is placed on Growth Hacking, Reinforcement Learning, and Web Data Mining.

Additionally, the Institute for Business Informatics bundles expertise in Data Governance, AI and IT Governance, conducts publicly funded consortium research at federal and state levels, and supports companies in implementing data-driven business models and governance structures.

At Heilbronn University of Applied Sciences, Human-Computer Interaction (HCI) is understood as a socio-technical research task that connects the development of digital systems with their usage contexts and structural change processes. The focus is on the design and evaluation of interactive systems that enable both innovative functions and suitable integration into complex social environments. Digital transformation processes are examined as an interplay of technology design, work practices, and framework conditions. User-centered and participatory approaches are linked with qualitative usage research and context-sensitive system design.

The UniTyLab develops new user interfaces and interaction technologies in the field of human-computer interaction and systematically transfers existing concepts into new application scenarios. Additionally, the Lab for Socioinformatics investigates the interactions between digital technologies and social structures as well as their influence on cooperation and communication in different contexts. The H-InfaM bundles research and teaching activities in the field of applied market research, develops new methodological approaches to market, opinion and social research, and supports companies and institutions through application-oriented analyses on specific issues.

This creates a research field that understands and further develops digital systems as designable elements of social change processes.

Quantum computing is dedicated to the research and application of quantum-based technologies to solve complex challenges in health and digital living environments. It deals with the question of how quantum algorithms, quantum simulations, and hybrid quantum-classical systems can be used to process large amounts of data in medicine, optimize personalized therapies, and accelerate population-based health analyses. The planned Laboratory for Applied Quantum Computing plays a central role in this endeavor, bringing together these approaches in interdisciplinary research contexts, testing them under realistic conditions, and promoting their transfer into innovative health technologies. In fall 2026, HHN will also receive its first quantum computer with superconducting technology from manufacturer IQM at the TechCampus, which will form the heart of the laboratory and be used for practical applications.

This research- and practice-oriented competence base also forms a solid foundation for scientific education in the field of quantum computing. In close cooperation with the MOLIT Institute for Personalized Medicine and as a member of the state initiative QuantumBW, transfer formats such as QC courses, winter schools, and lecture series are offered for students.

The experts include Professor David Kreplin, who researches quantum physics and applications in medical informatics, Professor Alexander Windberger, who is dedicated to Quantum Health Data Science, and Research Professor Javier Villalba-Diez, who develops geometric-topological models for quantum high-performance computing and resource theories.

•     Innovative software systems for technology-supported teaching, learning and testing in medicine and the health professions
•     Intelligent software and assistance services for support in the workplace

"My motivation as a researcher is to make people smarter and healthier through the development and use of innovative software!"

•     Process optimization and automation through artificial intelligence
•     Development of methods for the traceability of AI systems 
•     Applied game and decision theory

"AI systems are increasingly influencing our decisions and society. The modelling, optimization and investigation of AI-based decisions is essential in order to understand and help shape future developments. I would like to contribute to this."

•    Natural Language Processing and Conversational AI to support knowledge work
•    AI-based knowledge retention and knowledge transfer for learning organizations
•    Resource-efficient methods of machine learning

"The digital transformation, and in particular the use of artificial intelligence, is fundamentally changing the world of work. Cognitive assistance systems keep the focus on people and support them in their activities by procuring and providing relevant information in a context-specific manner."

•     User-oriented IT development
•     Leadership and collaboration in digitalization
•     Innovation methods

"In my research, I deal with the design of interactive technologies from a psychological perspective. My focus is on the technology development process, I explore how people and teams in IT can develop their full potential or how positive user experiences can be made possible for various target groups."

•     Web security, in particular authentication and authorization protocols (SAML, OAuth and OpenID Connect)
•     Applied cryptography
•     Cybersecurity in medicine

"The threats in cyberspace are higher than ever before. With my research, I want to contribute to making our (digital) world safer in a sustainable way."

•     Usability engineering
•     Augmented and virtual reality 
•     Innovative interaction technologies

"The interaction and collaboration between humans and technology is a very exciting, innovative and interdisciplinary field of research. New technologies such as virtual and augmented reality are increasingly finding their way into all areas of our lives. These new technologies must be developed to meet the needs of people and their tasks."

•     Methods and technologies of digitalization
•     Application scenarios and case studies of digitalization
•     Effects on mediation concepts

"I am interested in the effects of digitalization from both a methodological and a technological perspective. I look at the effects in specific professional fields of application as well as on teaching (both in terms of content and methodology) at universities. I examine both the changes themselves (descriptively) and the social and societal effects."

•     Biomarkers for mental and neurodegenerative diseases
•     Modeling cognitive processes in the human brain
•     Empirical methods and machine learning techniques

"In order to even begin to understand the complexity of our brain, we have to think across disciplines and individual methods. All of this is held together by computer science, which lays the foundations for this research using methods for data collection, storage and processing."

•     Health economic analysis models
•     Machine learning methods
•     Data analysis in the medical and epidemiological field

"The digital transformation puts people at the center and finds effective and economical solutions for the medicine of the future."

•     Development of sustainable procurement and value creation processes in the industrial, service and public sectors
•     Development of relevant future skills for the implementation of sustainable procurement and value creation processes
•     Sustainable process optimization in small and medium-sized enterprises using digital solutions

"Sustainable procurement is one of the most important levers for implementing holistic sustainable solutions in the industrial value creation process. It is the multiplier in the entire upstream value chain and enables sustainable solutions to spread across sectors far beyond a company's own operations".