Daniel R. Mendat
Papers
1
Total Citations
9
H-Index
1
About
Daniel R. Mendat is a pioneering researcher in neuromorphic engineering, specializing in spike-based processing, retinomorphic vision, and closed-loop control systems for autonomous robotics. His most notable contribution is the development of a neuromorphic self-driving robot that integrates an Asynchronous Time-based Image Sensor (ATIS) for retinomorphic visual sensing with IBM's TrueNorth neurosynaptic processor for real-time, spike-based data processing. This work, published in 2017, demonstrates a fully event-driven pipeline from perception to control, achieving efficient, low-power autonomous navigation—a landmark achievement in neuromorphic robotics. With 9 citations, this paper has influenced subsequent research in bio-inspired autonomous systems and edge computing. Mendat's interdisciplinary approach bridges computational neuroscience and robotics, advancing the field toward energy-efficient, brain-inspired machines. His contributions are particularly impactful for students and researchers exploring neuromorphic hardware, event-based vision, and autonomous systems, offering a compelling proof-of-concept for spike-based closed-loop control in real-world applications.
Research Focus
Key Achievements
Top Papers
- 1