Tiny Machine Learning Systems and Applications.
- Andrea Albanese received his B.S. in electrical and telecommunication engineering and his M.S. in mechatronics engineering with electronics and robotics pecialization from the University of Trento in 2017 and 2020, respectively.
- His main research focus is tiny machine learning, which involves deep neural network optimization techniques for resource-constrained environments such as microcontrollers. He is working on autonomous navigation systems applied to unmanned small vehicles by using tiny neural networks, deep learning, and online learning systems.
- He was involved for three years in the university Formula Student team with duties on power systems and embedded systems.
- Fully integrate online learning capabilities into smart systems based on deep neural networks with low-cost and low-power hardware (e.g., microcontrollers).
- andrea.albanese [at] unitn.it