Christian Mayr

About

Christian Mayr is a leading figure in neuromorphic computing and energy-efficient hardware design, with a focus on bridging the gap between biological neural networks and silicon systems. His major contributions center on developing low-latency, low-power architectures for real-world applications, as demonstrated by his highly cited 2021 work comparing Intel’s Loihi with a SpiNNaker 2 prototype for keyword spotting and adaptive robotic control—a study that has garnered 50 citations for its practical insights into neuromorphic benchmarking. Mayr has also pioneered power-adaptive 60 GHz receivers in 22 nm FD-SOI CMOS for Tactile Internet applications, enabling compact wireless robotic skins with unprecedented energy efficiency. His work on flexible, stretchable redistribution layers with embedded chips advances human-machine interfaces, facilitating seamless collaboration between biological and technical systems. With a portfolio spanning neuromorphic chips, adaptive control, and stretchable electronics, Mayr’s research is foundational for next-generation edge AI and robotic systems, earning him recognition as a key innovator in low-power, real-time neural processing.

Research Focus

Key Achievements

Top Papers

1. 1
   Comparing Loihi with a SpiNNaker 2 prototype on low-latency keyword spotting and adaptive robotic control

   50 citations · 2021
2. 2
   Designing a Power and Speed Adaptive 60 GHz Receiver in 22 nm FD-SOI CMOS for Tactile Internet Applications

   7 citations · 2024
3. 3
   Flexible and stretchable redistribution layer with embedded chips for human-machine interface

   4 citations · 2020
4. 4
   Low-Power Low-Latency Keyword Spotting and Adaptive Control with a SpiNNaker 2 Prototype and Comparison with Loihi

   4 citations · 2020

Key Collaborators

Contact & Links