Datenintegration fĆ¼r KI-gestĆ¼tzte Fertigungs- und ERP-Analysen bei Schilderwerk Beutha
2939
Matthias Baumgart
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7
Team members
12
Innovation projects
10
Partnerships
9
Courses
35
Publications
People, skills and shared ideas
Our team
Prof. Dr.-Ing. Matthias Baumgart has been appointed to the post of āDigital Integrated Process Managementā at Mittweida University of Applied Sciences. He brings to his role his specialist expertise in computer science, Project and Process Management, and machine learning, as well as his many yearsā experience in research management. Alongside his research and teaching activities, Prof. Baumgart is committed to innovative research projects, academic spin-offs and the promotion of early-career researchers, particularly within the framework of collaborative PhD programmes. Matthias Baumgart completed his PhD (Dr. Ing.) at the Faculty of Computer Science at Chemnitz University of Technology. As part of his doctoral thesis, he explored machine-based methods for developing a methodological framework for the evaluation of scientific texts. The focus was particularly on the automated analysis of text data and the use of machine learning methods in structured evaluation and decision-making processes. Matthias Baumgart began his professional career with an apprenticeship as a state-certified technical assistant in computer science, specialising in network technology. He subsequently studied as a Business Engineer, with a focus on Project and Process Management (M.Sc.), and completed a certificate programme to become a patent engineer.
- Member of the Senate
- Member of the Institute for Computer Science and Media in Research and Transfer (CSMRT)
- Member of the AI Working Group
- Head of the Doctoral Programme
- Member of the Faculty Council of the Faculty of Applied Computer Sciences and Biosciences
- Treasurer of the Society for the Promotion of Computer Science at Mittweida University of Applied Sciences e.V.
- Member of the Institute for Knowledge Transfer and Digital Transformation (IWD)
Understand, apply, create
Learning & Teaching
The course focuses on combining computer science, digital process management and modern methods of artificial intelligence with specific real-world problems. Students are expected not only to understand and analyse digital processes, but also to learn to identify opportunities for optimisation, select appropriate technical methods and develop solutions independently. In doing so, theoretical foundations are combined with practical applications, enabling students to follow and shape the entire process ā from analysing a problem, through designing a solution, to its technical implementation.
Particular emphasis is placed on an application- and project-oriented approach to teaching and learning. Topics such as process automation, process optimisation, machine learning, data analysis and Software Development are taught using real or realistic-world tasks and tested in practice. Students learn to apply data and digital technologies in a targeted manner, to systematically analyse complex processes, and to evaluate ML and RAG-based methods in terms of their potential applications and limitations. Through work on specific projects, the programme fosters not only technical skills but, in particular, analytical thinking, problem-solving skills and the ability to independently develop and evaluate digital solutions.
āFor whatever one must first learn before one can carry it out, one learns by carrying it out.ā
ā Aristotle, Nicomachean Ethics, Book II
Digitisation of specific teaching content
Subject content is translated into digital teaching and learning resources in a pedagogically sound manner. Students select appropriate media and interactive formats, implement them technically and evaluate their effectiveness.
Introduction to Computer Science I
This course provides an introduction to the formal foundations and ways of thinking in computer science. It covers number systems, data representation, logic, algorithmic thinking and basic programming constructs, as well as the core skills required for project work.
Research Management
This course covers the key structures, methods and processes of research management through practical tasks. Students learn to systematically structure research projects from the initial idea through planning and application to implementation and monitoring. In doing so, they examine organisational, administrative and funding-related frameworks and develop an understanding of the interplay between academic objectives, project organisation, resources and knowledge transfer.
Interdisciplinary Knowledge Acquisition and Communication I
Students draw on knowledge from products developed across various disciplines and present this in a structured manner. Particular emphasis is placed on the clear visualisation and communication of complex concepts in a way that is tailored to the target audience.
The internationalisation of digital teaching materials
Digital teaching materials are adapted linguistically, culturally and technically for international audiences. The focus is on localisation, intercultural media design, accessibility and distribution via digital platforms.
Science and Business I
Students explore the links between academic research and business practice. In doing so, they learn to contextualise academic findings within practical contexts and to assess their significance for businesses and organisations. Particular emphasis is placed on developing an understanding of the transfer of knowledge and innovation, as well as collaboration between academia and industry.
Science and Business II
Students deepen their understanding of collaboration between academia and industry and explore the practical application of scientific findings. In doing so, they learn to apply scientific findings to specific problems and to identify opportunities for innovative applications. Particular emphasis is placed on knowledge transfer, the development of application-oriented solutions and the assessment of innovation potential.
Science and Business III
In the third WW module, students apply their knowledge of the interface between science and business to specific issues and practical scenarios. In doing so, they develop and evaluate their own approaches to translating scientific findings into practice. Particular emphasis is placed on working independently on application-oriented tasks and developing sustainable solutions at the interface between science, business and society.
Science and Business IV
Students independently apply scientific findings to complex real-world problems and use them to develop practical solutions. In doing so, they examine the requirements and framework conditions of knowledge transfer and reflect on the application of scientific findings in economic and social contexts. Particular emphasis is placed on the independent development, implementation and evaluation of knowledge transfer and innovation projects.
Theses offer the opportunity to combine oneās own interests with current issues in research and practice. Students can either take up existing topics from the chairās research areas or contribute their own ideas and work together to develop them into a suitable academic research question.The focus is on projects that involve not only theoretical analysis but also design, development, testing or evaluation. In doing so, technological, organisational and economic perspectives can be integrated:
- AI-supported assistance and information systems, machine learning
- Large language models and retrieval-augmented generation
- Digitalisation and automation of processes
- IT-supported Project and Process Management
- Data analysis and intelligent information processing
- Semantic search and knowledge management
- Multimodal information processing
- Development and evaluation of interactive systems
- Gamification and digital learning systems
- Research management and research information systems
- Technology, knowledge and innovation transfer
Proposals for your own research topics are expressly welcome. The key requirement is that these can be developed into a clearly defined research question of academic merit with a recognisable practical application.
Bringing perspectives together, shaping innovation
Network-based research
Digital Integrated Process Management focuses on the question of how digital technologies can be used to understand complex processes, develop them in a targeted manner and support them intelligently. The starting point is a systematic review of existing processes: processes are analysed, interrelationships are made visible and opportunities for more efficient design are identified. Building on this, digital methods are employed to automate processes, link them together and adapt them to changing requirements.
Artificial intelligence and data-driven methods play a particularly important role in this context. Data is understood not merely as the output of digital processes, but as the basis for analysing processes, recognising patterns and deriving new courses of action. Machine learning, automated data processing and intelligent analytical methods open up new possibilities for mapping complex interrelationships and further developing digital processes. This ranges from the analysis of human activities and movement data to the development of digital models and technical applications.
The research combines these methodological approaches with specific application scenarios. The focus is on solutions that do not view digital processes in isolation, but take into account the interplay between people, data, software and technical systems. This gives rise to application-oriented concepts for process optimisation, automation and intelligent decision support, which combine scientific methods with practical requirements from research, business and society.
āI see research as a collaborative endeavour. It becomes particularly powerful when different perspectives, skills and experiences come together. Cooperation creates the space in which ideas can be turned into viable solutions.ā
ā Prof. Dr.-Ing Matthias Baumgart
Partners in research and teaching
Bringing expertise together, broadening perspectives
Research thrives on the exchange of different perspectives and expertise. That is why we work closely with other departments. Through joint projects, teaching programmes and research initiatives, we combine our specialist areas of focus and develop new approaches at the intersections of computer science, digitalisation, media and other fields of application.
Mittweida University of Applied Sciences
Data only becomes meaningful once it is understood. The Chair analyses diverse data sets, makes them accessible using methods from artificial intelligence and media informatics, and translates them into applications that support decision-making.
Mittweida University of Applied Sciences
A pair of glasses, a gesture in the air, and the machine responds. The research group is developing immersive applications for industry, education and culture, and is testing how user-friendly they actually are.
Practice partnerships
Science in dialogue with the professional world
Close collaboration with businesses, public institutions and other partners in the field is a key part of our work. Together, we translate scientific findings into concrete practical applications, develop new approaches and address current issues arising from the field. This generates impetus for research projects, courses, dissertations and long-term collaborations.
Industrial Data Layer fĆ¼r KI-basierte Prozessanalysen
2941
Christian Roschke
KI@EINS Projekte
2937
Matthias Baumgart
PlattformĆ¼bergreifende Mitarbeiterapp fĆ¼r den SAXONIA-Verbund
2938
Matthias Baumgart
TransferLotse Mittelsachsen ā Entwicklung eines digitalen Assistenzsystems zur intelligenten Vernetzung von regionaler Wirtschaft und Wissenschaft
2942
Christian Roschke
Efficient Real-Time Point Cloud Rendering in Unity Using Incremental Spatial Sorting
21857
konferenzpaper
Teaching Sustainability through Gamification: An Empirical Study with Student Perspectives in Vocational Education
Appeared in: Economic Sciences 21 (2026), P. 242 ā 255
DOI: 10.69889/hh8m5w14
21629
konferenzpaper
Development and Evaluation of a Feature for a University Application to Increase Motivation and Reduce the Dropout rate of Students in Higher Education
Presented on: Ireland International Conference on Education (IICE-2025), 2025
21320
konferenzpaper
E-Sport an Hochschulen. Eine Studie zur Nutzungsintention digitaler Spiele von Studierenden im Hochschulsport
Appeared in: GesellschaftsphƤnomen E-Sport ErklƤrungs- und ForschungsbeitrƤge aus einer interdisziplinƤren Perspektive., 2025, P. 71 ā 105
21393
sammelbandbeitrag
E-Sport an Hochschulen. Eine Studie zur Nutzungsintention digitaler Spiele von Studierenden im Hochschulsport
Appeared in: GesellschaftsphƤnomen E-Sport. ErklƤrungs- und ForschungsbeitrƤge aus einer interdisziplinƤren Perspektive, 2025, P. 71 ā 105
21396
sammelbandbeitrag
Developing new ideas together
Thank you very much for your interest in our work and in the topics relating to Digital Integrated Process Management. It is particularly where different disciplines, technologies and application perspectives come together that new approaches to the design and further development of digital processes emerge.
If you are interested in our research, would like to contribute your own research questions, or wish to develop and test digital solutions together with us, we look forward to hearing from you. Whether itās process optimisation, automation, data analysis or the use of artificial intelligence ā we are open to new ideas, collaborative research approaches and practice-oriented projects. Interdisciplinary questions are particularly welcome.
We can only see a short way ahead, but we can already recognise much of what needs to be done.
ā Alan Turing, Computing Machinery and Intelligence, 1950
New ideas emerge where different perspectives come together. Research becomes more impactful when knowledge is shared and developed collaboratively. Do you have an idea, a research question or an interest in collaborating? Please feel free to get in touch.