Daniele Jahier Pagliari
Papers
2
Total Citations
37
H-Index
2
About
Daniele Jahier Pagliari is a leading researcher at the intersection of embedded artificial intelligence and ultra-low-power computing, with a focus on enabling complex machine learning on resource-constrained devices. His work primarily targets human-machine interaction and autonomous systems, where he has made significant contributions to gesture recognition and onboard intelligence for miniaturized robots. Pagliari’s 2022 paper on "Bioformers" (30 citations) pioneered the use of Transformer architectures for ultra-low-power sEMG-based gesture recognition, a breakthrough for non-invasive prosthetic control and rehabilitation tasks. In 2023, he advanced autonomous nano-UAVs with a paper on deep neural network architecture search for visual pose estimation (7 citations), addressing the challenge of running accurate computer vision on sub-100 gram drones. His research consistently pushes the boundaries of energy-efficient deep learning, achieving state-of-the-art performance on milliwatt-scale hardware. Pagliari’s work has been recognized for its practical impact on wearable technology and robotics, making him a key figure in the growing field of tinyML and edge AI.
Research Focus
Key Achievements
Top Papers
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