Thematic Session 1

THEMATIC SESSION #1

Michael Kuhl

Mittweida University of Applied Sciences, Germany

• kuhl@hs-mittweida.de

Flaviana Tagliaferri

Mittweida University of Applied Sciences, Germany

• flaviana.tagliaferri@hs-mittweida.de

Maurice Rekrut

German Research Center for Artificial Intelligence, Germany

• maurice.rekrut@dfki.de

Mansi Sharma

German Research Center for Artificial Intelligence, Germany

• mansi.sharma@dfki.de

In complex and critical environments—ranging from industrial production lines to emergency response scenarios—effective human-machine interaction (HMI) is crucial for ensuring safety, enhancing decision-making, and improving operational efficiency. This special session will explore how advanced technologies, including Brain-Computer Interfaces (BCIs), extended reality (XR), artificial intelligence (AI), and sensor systems, can be integrated to optimize HMI in these demanding settings.

We invite contributions addressing recent innovations in HMI technologies that improve situational awareness, enhance human capabilities, and facilitate seamless interaction between humans and machines. This includes not only BCIs, but also adaptive user interfaces, multimodal interaction techniques, and automated systems that assist in critical tasks. Real-world applications may include but are not limited to mobility (e.g., logistics and transportation), industrial production (e.g., smart factories), and emergency response operations (e.g., disaster management).

The session will highlight how these advancements support human operators in high-pressure, dynamic environments, ensuring safer, more efficient workflows while enabling resilience in unpredictable conditions. By fostering collaboration between humans and machines, these technologies promise to transform how we manage complex, high-stakes situations in real-world environments.

Topics of interest for this Thematic Session include (but are not limited to):

• Human-Machine Interaction;
• Artificial Intelligence for HMI;
• Artificial Intelligence for safety;
• Intelligent Sensor System for Safety;
• Smart feedback actuator;
• Decision Support Systems based on AI;
• Innovative sensor system for hazard evaluation;
• Virtual and augmented reality for hazard evaluation;
• Wearable sensors for safety.

Michael Kuhl, studied Electrical Engineering at TU Chemnitz and TU Delft, starting in 1991 and graduating in 1996 with research investigations at the Delft Institute of Microsystems and Nanoelectronics. From 1996, he worked as a development engineer in the electronics industry before moving to research at the Fraunhofer Gesellschaft in 2001. In 2003 he established the group of Process Informatics at the Fraunhofer Institute for Machine Tools and Forming Technology. His work was focused on quality and process monitoring in production technology. After achieving his doctorate in 2010 he became the Head of the Main Department of Production Technology at the Professorship for Machi ne Tools and Forming Technology at TU Chemnitz. In 2012 he became the Managing Chief Engineer for Research and Development at Fraunhofer IWU and since January 2015 he has been the Division Director for Strategy and International Affairs.
Since 2017, he has been a Full Professor at Mittweida University of Applied Sciences (HSMW). His Chair for Systems Electronics is engaged in the development of electronic systems for production engineering and ambient assisted living. Since 2019 he has been the Dean of Studies of the Bachelor's degree in Electrical Engineering Automation at the HSMW. Since 2024 he has been the Dean of Faculty Engineering Sciences at the HSMW.

Flaviana Tagliaferri graduated in 2008 with the best score in Mechanical Engineering at ‘Tor Vergata’ University, Rome (Italy).
Between 2006 and 2009 she worked for IACOBUCCI HF Electronics S.p.A. company, operating in the aerospace sector. After achieving her doctorate in 2012 at the University of Naples ‘Federico II’ (Italy) she won a Post-Doc grant (funded by DAAD - Deutscher Akademischer Austauschdienst) to work at the Institute for Machine Tools and Production Processes (IWP) of Chemnitz University of Technology, (TU Chemnitz, Germany). Her focus was on innovative cutting technology. From 2012 to 2017 she worked as a research fellow at the Department of Industrial Engineering University of Naples, Federico II. At the same time and until 2018 she was a research associate at IWP of TU Chemnitz. Since July 2017 she has been a lecturer at Niccolò Cusano University, Rome (Italy), teaching ‘Manufacturing materials and technologies for the food industry’. Since October 2018 she has been a researcher at the Mittweida University of Applied Sciences, under the chair for Systems Electronics, and a lecturer , teaching ‘Industry 4.0 - Responsible Consumption and Production’.

Dr. Maurice Rekrut is a senior researcher at the German Research Center for Artificial Intelligence (DFKI). He graduated in Biomedical Engineering at the University of Applied Sciences Saarland (HTW Saarland) with focus on Neural Engineering and received his MSc in 2013. Since then, he has been working as a full-time researcher at DFKI in the Cognitive Assistants research department. His research is concerned with non-invasive Brain-Computer Interfaces (BCIs) and their applicability in real-world use cases. Since 2020 he is the head of the Cognitive Assistants BCI-lab at DFKI Saarbrücken, where established BCI concepts are revised with respect to integration in to practical applications and new methods are developed to extend and improve existing BCI paradigms. One focus is on the recognition of imagined and spoken speech with EEG-based BCIs which was also the topic of his PhD in Computer Science which he received in 2023 from Saarland University.

Mansi Sharma is a full-time researcher at the German Research Center for Artificial Intelligence (DFKI) and Ph.D. student at Saarland University. She received her MSc degree in Computer Science from Saarland University in 2020. Her primary research focuses on human intent recognition and multimodality interaction, especially with non-invasive Brain-Computer Interfaces (BCIs). She participated in several BCI competitions and was awarded first prize in Imagined Speech Classification hosted by the International Winter Conference on Brain-Computer Interfaces.