Dipl.-Ing. Alexey Serdyuk

Dipl.-Ing. Alexey Serdyuk

  • Engesserstr. 5

    76131 Karlsruhe

Research interests

Neuromorphic computing architectures

Neuromorphic computing is inspired by biological neural networks and tries to mimic their behavior precisely. Neuromorphic neural networks have advantage over conventional artificial neural networks in their power efficiency and asynchronous, self-adapting nature. Being firstly introduced in the last century, neuromorphic computing is actively rediscovered due to recent advances in the neurobiology, physics, semiconductor technology and AI. But the way neuromorphic architectures work poses new challenges and requires new approaches to the data representation, training, AI-frameworks and tools.

AI in embedded systems

Artificial intelligence is actively adopted in the design of embedded systems. Embedded AI helps localize data flows, needed for training neural networks, what in turn helps to offload the servers, communication network infrastructure and retain the privacy of personal data. With a broad range of existing solutions for AI-accelerated SoCs, it is still challenging to integrate AI into resource constrained systems, due to complexity of neural networks used in industry. Therefore, new optimization techniques on the hardware as well as on the software side have to be researched.

Publications


2023
Conference Papers
A Unified SoC Lab Course: Combined Teaching of Mixed Signal Aspects, System Integration, Software Development and Documentation
Pfau, J.; Leys, R.; Neu, M.; Serdyuk, A.; Peric, I.; Becker, J.
2023. 2023 IEEE International Symposium on Circuits and Systems (ISCAS), 5 S., Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISCAS46773.2023.10181679
2022
Conference Papers
Hardware-aware Workload Distribution for AI-based Online Handwriting Recognition in a Sensor Pen
Kreß, F.; Serdyuk, A.; Hotfilter, T.; Höfer, J.; Harbaum, T.; Becker, J.; Hamann, T.
2022. 2022 11th Mediterranean Conference on Embedded Computing (MECO). Ed.: IEEE, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/MECO55406.2022.9797131