Iris Fürst-Walter, M. Sc.

Iris Fürst-Walter, M. Sc.

  • Engesserstr. 5
    76131 Karlsruhe

Research interests

Artificial intelligence in embedded systems

Artificial intelligence has found its way into many areas to make systems more precise and reliable than previous manually optimized algorithms. One common method is machine learning, which learns to solve predefined tasks on its own based on a large database. But for artificial intelligence to enrich the end application, it must be embedded. A particular challenge here is to compress the networks in such a way that, on the one hand, energy efficiency on the target platform increases and, on the other hand, accuracy is maintained.

Smart Textiles

During training, many athletes already wear fitness trackers to record body parameters, step counts or daily activity. The ITK Innovation & Venture Lab is going one step further and researching smart textiles for motion detection and assessment. For this purpose, inertial measurement units (IMUs) for recording upper body movement have already been textile-integrated into a shirt. With an eye toward protecting private data while keeping power consumption low in the shirt, edge versus remote solutions are weighed against each other.

 

Assistive Robotics

Many people strive for a long, self-determined life within their own four walls. However, the care crisis means that human care in the home is becoming increasingly rare. As an alternative, KIT is researching assistive robots that help elderly people to cope with everyday life at home. Important aspects for increasing their acceptance are short response times and personalization of the services. For this purpose, ITIV is researching suitable hardware accelerators with low latencies and a high degree of privacy.

 

Supervised student work (selection)

  • MA: "Konzeptioneller Entwurf eines modularen Sensornetzwerks für intelligente Textilanwendungen"
  • MA: "Datenanalyse von Sensorinformationen in intelligenten Textilanwendungen"
  • MA: "Structured Analysis of a Deep Neural Network for Face detection for Implementation on FPGAs"
  • MA: " Design and Analysis of an Intelligent Sensor Network for Motion Tracking"
  • MA: "Design and Analysis of a Human Pose Estimation System from Sparse IMU-Sensing"
  • MA: "Efficient Design of 3D-CNN-Acceleration on FPGA for Action Recognition"
  • BA: "Analysis of concepts for an AI-based system for automated identification and assignment of machine parameters"
  • SA: "IMU-based Action Recognition using Machine Learning"

Publications


2023
Journal Articles
CNNParted: An open source framework for efficient Convolutional Neural Network inference partitioning in embedded systems
Kreß, F.; Sidorenko, V.; Schmidt, P.; Hoefer, J.; Hotfilter, T.; Walter, I.; Harbaum, T.; Becker, J.
2023. Computer Networks, 229, Article no: 109759. doi:10.1016/j.comnet.2023.109759
Conference Papers
Automated Search for Deep Neural Network Inference Partitioning on Embedded FPGA
Kreß, F.; Hoefer, J.; Hotfilter, T.; Walter, I.; El Annabi, E. M.; Harbaum, T.; Becker, J.
2023. Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Hrsg.: I. Koprinska. Pt. 1, 557–568, Springer International Publishing. doi:10.1007/978-3-031-23618-1_37
2022
Conference Papers
Hardware-aware Partitioning of Convolutional Neural Network Inference for Embedded AI Applications
Kreß, F.; Hoefer, J.; Hotfilter, T.; Walter, I.; Sidorenko, V.; Harbaum, T.; Becker, J.
2022. 18th International Conference on Distributed Computing in Sensor Systems (DCOSS), 133–140, IEEEXplore. doi:10.1109/DCOSS54816.2022.00034
Embedded Face Recognition for Personalized Services in the Assistive Robotics
Walter, I.; Ney, J.; Hotfilter, T.; Rybalkin, V.; Hoefer, J.; Wehn, N.; Becker, J.
2022. Machine Learning and Principles and Practice of Knowledge Discovery in Databases – International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I. Ed.: M. Kamp, 339–350, Springer International Publishing. doi:10.1007/978-3-030-93736-2_26