Teaching Offerings

This lecture introduces key concepts and principles of interactive systems from a human and computer perspective. Furthermore, it describes core development processes for interactive systems as well as provides insights on the use & contexts of interactive systems with a specific focus on selected application areas in organisations and society.

With this lecture, students acquire foundational knowledge to successfully design of the interaction between human and conputers in business and private life. The course is complemented with a design capstone project, where students in a team select and apply design methods & techniques in order to create an interactive prototype.

Computers have evolved from batch processors towards highly interactive systems. With the rapid progress in the field of artificial intelligence, computers can now learn and adapt to their environment, simulate human intelligence processes as well as support or even take over tasks from humans. This offers great possibilities, but at the same time raises new challenges for the successful design of interactive systems.  The aim of this course is to introduce advanced concepts and theories as well as current practice of designing interactive systems. A specific focus is set on designing AI-based interactive systems for individuals and groups at work ranging from personal productivity assistants to AI-augmented virtual collaboration.

The course is complemented with hands-on exercises and a design capstone project in cooperation with an industry partner. In the project, students in a team effort apply state-of-the-art design methods & techniques and create an interactive system design prototype with a specific focus on human-AI interaction.

This course introduces key concepts and state-of-the-art engineering principles for interactive systems. Specifically, the human-centered design process is introduced and contextualized with a specific focus on biosignal-based adaptive systems. The lectures introduces wearable technologies and biosignal intelligence (leveraging Artificial Intelligence on sensor data to analyze human activities).

The course is complemented with an engineering capstone project, where students work in a team with real-world use cases in order to realize a prototypical biosignal-based adaptive system using state-of-the-art wearable technologies (e.g., Smartwatches) as well as existing software libraries and APIs for biosignal processing and analysis. 

Data Science and Business Intelligence & Analytics (BI&A) systems go hand in hand and are a core enabler of decision-making in today’s organizations.  Where Data science rather represents a broad and generic concept of studying data to extract meaningful insights, BI&A systems provide actionable support along the entire analytical lifecycle. The aim of this course is to introduce key concepts, design principles, and building blocks of contemporary BI&A systems as well as foundational methods and central roles in organizations. A specific emphasis is set on introducing key concepts and activities from the perspectives of a data engineer, a data analyst, and a business analyst. 

The course is complemented with an engineering capstone project, where students work in a team with real-world use cases and data in order to create a prototypical Business intelligence & Analytics system using state-of-the-art technologies (e.g., scikit-learn in Python or Microsoft Power BI)

User-adaptive systems collect and analyze biosignals from users to recognize user states as a basis for adaptation. Thermic, mechanical, electric, acoustic, and optical signals are collected using sensors which are integrated in wearables, e.g. glasses, earphones, belts, or bracelets. The collected data is processed with analytics and machine learning techniques in order to determine short-term, evolving over time, and long-term user states in the form of user characteristics, affective-cognitive states, or behavior. Finally, the recognized user states are leveraged for realizing user-centric adaptations.  In this seminar, interdisciplinary teams of students design, develop, and evaluate a user-adaptive system prototype leveraging state-of-the-art hard- and software. This seminar follows an interdisciplinary approach. Students from the fields of computer science, information systems and industrial engineering & management collaborate in the prototype design, development, and evaluation.  The seminar is carried out in cooperation between Teco/Chair of Pervasive Computing Systems (Prof. Beigl) and the Institute of Information Systems and Marketing (h-lab, Prof. Mädche). It is offered as part of the DFG-funded graduate school “KD2School: Designing Adaptive Systems for Economic Decisions“ (https://kd2school.info/)

Research Seminar: Human-Centered Systems

Engineering Seminar: Human-Centered Systems

Digital Citizen Science is an innovative approach to conduct field research - interactively and in the real world with citizens. The seminar theses are interdisciplinary supervised by researchers from multiple institutes that are working together on the topic of Digital Citizen Science.  

The seminar is tightly connected to the initiative: wir.forschen.digital

The main goal of the thesis colloquium is to foster exchange between students (e.g., with similiar thesis topics or research methods). Furthermore, it is an opportunity for you to practice presentation and feeback-giving skills. Each thesis student of the research group is expected to attend the thesis colloquium.

This course introduces existing adaptive systems research in selected research communities and describe important concepts. Furthermore, we articulate major building blocks of biosignal based
adaptive systems and describe design/evaluation processes and activities. We classify different types of biosignals and describe key procedures for measuring, processing, classification, and interpretation. Finally, PhD students collect, process and analyze biosignals and design an adaptive systems prototype as part of the capstone project.