About
Matthias Ochs is a Researcher at the Chair of Circuit Design, Technical University of Munich (TUM), where he has been developing analog AI hardware for low-power smart sensors since January 2020. He holds an M.Sc. in Electrical Engineering and Information Technology from TUM, complemented by industry experience at Texas Instruments and Siemens.
Education:
- Apprenticeship as Electronics Technician for Energy and Building Services (2013)
- B.Sc. in Electrical Engineering and Information Technology, TUM (2017)
- M.Sc. in Electrical Engineering and Information Technology, TUM (2019)
His research specializes in ultra-low-power analog circuit designs for AI applications in energy-constrained environments. Key focus areas include spiking neural networks, vibration sensing, and energy-efficient hardware for smart sensors. His work bridges semiconductor technology and embedded AI systems.
Recent publications (2024) demonstrate a consistent emphasis on energy optimization in neural network hardware and industrial sensing. Trends include novel analog neuron designs, vibration analysis in mechanical systems, and circuit-level innovations achieving record-low power consumption (e.g., 86.9fJ/SOP).
He collaborates with the Chair of Circuit Design team under Prof. Ralf Brederlow, contributing to projects in neuromorphic hardware and sensor systems.
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