Academic Staff
Valeria Zitz
Profile
I am a PhD researcher at the TECO Lab (Karlsruhe Institute of Technology), working on the development of embedded wearable systems for personalized preventive healthcare. My research spans sensor technology, PCB design, and embedded signal processing to enable multimodal physiological sensing. Beyond diagnostics and biofeedback, I focus on non-invasive therapeutic applications such as photobiomodulation and thermal stimulation. By combining technical innovation with clinical validation and human-centered design, I aim to transform wearables into intelligent, comfort-optimized companions for diagnostics, therapy, and everyday health interventions.
Short CV
- since 2024 PhD Candidate at TECO
- 2023 – 2024 Researcher, Freie Universität Berlin
- 2023 M.Sc. Computer Science, Karlsruhe University of Applied Sciences
- 2022 – 2023 Technical Product Lead, EnBW Energie Baden-Württemberg AG
- 2022 – 2024 Lecturer for Human Computer Interaction, Karlsruhe University of Applied Sciences
- 2021 – 2024 Lecturer for Usability & Audiovisual Communication, Heilbronn University of Applied Sciences
- 2021 B.Sc. Computer Science, Karlsruhe University of Applied Sciences
- 2016 B.Sc. Journalism, Karlsruhe University of Applied Sciences
Research Interests
- Embedded Sensing & System Design
- Digital Biomarkers & Preventive Medicine
- Health Applications & Clinical Translation
Teaching
- Proseminar Mobile Computing & Seminar Ubiquitäre Systeme: SS2026, WS 2025/2026
- Proseminar Mobile Computing: SS 2025
- Praxis der Softwareentwicklung (PSE): WS 2024/2025
Projects
Theses
Recognition and Classification of Allergy-Related Events from Wearable Sensor Data
Allergy-related reactions such as eye rubbing, palate rubbing, swallowing, and throat clearing occur repeatedly throughout the day but are rarely documented reliably. This thesis aims to develop a machine-learning pipeline that automatically recognizes such events in continuous multimodal wearable-sensor data and subsequently classifies them into distinct reaction types. The proposed approach consists of two stages: Event recognition: Detecting when a potentially relevant event occurs within a continuous sensor stream.Event classification: Determining which type of allergy-related reaction occurred.
Hardware Design and Prototyping of a Wearable Device for Personal Air Quality Monitoring
Airable is a custom-built smart hair pin or necklace accessory that integrates miniature environmental sensors to support personal air-quality monitoring and pollen-allergy research. The goal of this thesis is to design and evaluate the a basic functional prototype, combining sensing, wireless communication, power management, and a wearable form factor.
Topic Areas
Publications
Zitz, V.; Küttner, M.; Hummel, J.; Knierim, M. T.; Beigl, M.; Röddiger, T.
2025. Proceedings of the ACM International Symposium on Wearable Computers (ISWC’25), 91–97, Association for Computing Machinery (ACM). doi:10.1145/3715071.3750421
Röddiger, T.; Zitz, V.; Hummel, J.; Küttner, M.; Lepold, P.; King, T.; Paradiso, J. A.; Clarke, C.; Beigl, M.
2025. CHI EA ’25: Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, Art.-Nr.: 713, Association for Computing Machinery (ACM). doi:10.1145/3706599.3721161