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About

Thomas Bruun Madsen is a rising researcher at the forefront of neuromorphic robotics, dedicated to bridging the gap between bioinspired computing and practical robotic systems. His key research areas include spiking neural networks (SNNs), low-power embedded systems, and the integration of neuromorphic hardware with conventional microcontrollers. Madsen’s major contributions center on developing accessible platforms that bring neuromorphic capabilities to standard, low-power CPU hardware—most notably through his 2023 paper on an interface platform for robotic neuromorphic systems (11 citations), which introduced a novel communication protocol for linking neuromorphic chips with traditional controllers. His 2024 work on implementing communication, computing, and control tasks for neuromorphic robotics on conventional hardware (4 citations) further demonstrated how SNNs can run efficiently on devices like the Raspberry Pi. Most recently, his 2025 paper on a self-learning neuromorphic robot based on reward-driven SNNs (1 citation) showcases a fully integrated system where robots learn from environmental feedback without external supervision. Madsen’s work is notable for its practical, cost-effective approach, making neuromorphic robotics more accessible to researchers and students working with limited resources.