CV
Education
- Ph.D. in Electrical Engineering, ETH Zurich, 2022
- Thesis: Near-Sensor Analytics and Machine Learning for Wearable Biomedical Systems (Defended on Nov. 29, 2022)
- Ph.D. Fellowship from Swiss Data Science Center
- Master of Science in Biomedical Engineering (Bioimaging), ETH Zurich, 2018
- Thesis: Embedded Classification of Neural Activity in Rat Cortex
- Bachelor’s degree (Laurea cum Laude) in Biomedical Engineering, Politecnico di Milano, 2016
- Thesis: Frequency Bands Analysis of fMRI Spontaneous Cortical Activity
- “Mobilità” national scholarship for excellent students (awarded to the best 100 students nationwide)
Publications
Embedded Classification of Local Field Potentials Recorded from Rat Barrel Cortex with Implanted Multi-Electrode Array Permalink
FANN-on-MCU: An Open-Source Toolkit for Energy-Efficient Neural Network Inference at the Edge of the Internet of Things Permalink
HR-SAR-Net: A Deep Neural Network for Urban Scene Segmentation from High-Resolution SAR Data Permalink
InfiniWolf: Energy Efficient Smart Bracelet for Edge Computing with Dual Source Energy Harvesting Permalink
An Accurate EEGNet-based Motor-Imagery Brain–Computer Interface for Low-Power Edge Computing Permalink
Q-EEGNet: An Energy-Efficient 8-bit Quantized Parallel EEGNet Implementation for Edge Motor-Imagery Brain–Machine Interfaces Permalink
EEG-TCNet: An Accurate Temporal Convolutional Network for Embedded Motor-Imagery Brain–-Machine Interfaces Permalink
Mixed-Precision Quantization and Parallel Implementation of Multispectral Riemannian Classification for Brain–Machine Interfaces Permalink
Leveraging Tactile Sensors for Low Latency Embedded Smart Hands for Prosthetic and Robotic Applications Permalink
Reducing Neural Architecture Search Spaces with Training-Free Statistics and Computational Graph Clustering Permalink
An Energy-Efficient Spiking Neural Network for Finger Velocity Decoding for Implantable Brain-Machine Interface Permalink
Exploring Automatic Gym Workouts Recognition Locally on Wearable Resource-Constrained Devices Permalink
Nonlinear and machine learning analyses on high-density EEG data of math experts and novices Permalink
Enhancing Performance, Calibration Time and Efficiency in Brain-Machine Interfaces through Transfer Learning and Wearable EEG Technology Permalink
MI-BMInet: An Efficient Convolutional Neural Network for Motor Imagery Brain–Machine Interfaces With EEG Channel Selection Permalink
Minimizing artifact-induced false-alarms for seizure detection in wearable EEG devices with gradient-boosted tree classifiers Permalink
BrainFuseNet: Enhancing Wearable Seizure Detection Through EEG-PPG-Accelerometer Sensor Fusion and Efficient Edge Deployment Permalink