Education

ETH Zürich, Zürich, Switzerland
MSc. Electrical Engineering and Information Technology
2019-2021
  • Main Track: Embedded Systems, Low-power Design, Sensors and Sensor Fusion, TinyML
  • Additional Topics: Machine Learning, Computer Vision, VLSI, System and Network Security

Polytechnic of Turin, Turin, Italy
BSc. Electronic Engineering
2016-2019
  • Fundamentals: Analysis, Mathematical Methods, Physics, Informatics and Chemistry fundamentals.
  • Field-Specific: Solid State Devices, Analog Circuits, Electromagnetic Fields, Digital System Design, OOP.
  • Extracurricular: Member of the PoliTOcean student team, developing a water ROV for the international MATE ROV competition. Tasks included PCB design, debugging and assembly, and firmware development.

Liceo Salesiano Valsalice, Turin, Italy
Highschool Scientific Diploma
2011-2016

Work Experience

Skaaltec, Founding Engineer/Technical Lead/CTO
2024-now

At Skaaltec, I drive technical innovation in neurorehabilitation technology, coordinating development across hardware, firmware, and system integration. I provide technical direction for critical components while harmonizing cross-functional workflows to advance product development efficiently. Key contributions:

  • System Design: Designed and developed two complementary, wirelessly-connected devices: an ultra-low power motion tracking system with embedded fusion algorithms, and a transcutaneous nerve stimulator with precise current-controlled pulse generation capabilities.
  • Technical Direction: Established development roadmaps for system components, defined technical specifications based on medical requirements (IEC 60601), and coordinated integration between hardware, utility software, and cloud components.

ETH Zürich - Center for Project-Based Learning, Scientific Assistant
2021-2024

In this inter-disciplinary research environment, I developed rigorous scientific methodology and literature-based approaches to rapidly master new technical domains. My research spanned multiple technical domains:

  • TinyML and Sensor Fusion: Developed complete embedded systems powered by TinyML and novel sensors for research applications, including real-time audio applications (Voice Activity Detection), gesture recognition, eye-tracking, and motion classification.
  • Low-power Embedded and Bluetooth-LE: Designed and implemented resource-constrained prototypes for battery-operated devices with strict dimensional and energy limitations, focusing on sensing capabilities, real-time signal processing chains, and efficient Bluetooth communication protocols.
  • mmWave Radar: Pioneered applications of mm-Wave radar technology across multiple domains: biomedical applications (contactless vital sign monitoring), human-machine interfaces (gesture recognition), and advanced perception systems for autonomous robotics.

Concurrently supervised almost 20 student theses, defining research objectives aligned with laboratory goals, establishing project milestones, and providing technical mentorship to ensure successful outcomes. This supervision expanded my research impact while developing leadership skills in technical team management.


Microtecnica S.r.l., Summer Intern
2015
Summer internship in the Engineering Area. I analysed data from public databases to evaluate the Mean Time Between Failure (MTBF) of aircraft components to improve reliability.

Key Projects

SmartVNS (Skaaltec), Startup
2025
Architected and developed a comprehensive neurorehabilitation platform combining precise motion tracking with transcutaneous nerve stimulation technology. Designed the hardware architecture with safety-critical requirements within medical specifications, implemented firmware for real-time processing and device synchronization.

Wearable Sensing Technologies, Research Projects
2021-2024
Designed and implemented wearable prototypes with different sensing modalities, including (1) A motion-tracking bracelet with IMU and magnetometer sensor fusion for orientation estimation, (2) An sEMG-based gesture recognition system, and (3) An in-ear PPG sensor with a custom front-end.

Wearable Gesture Recognition with Novel Short-Range Radars, Research Project
2021
Developed a complete wearable earbud device for contactless gesture recognition utilizing novel low-power radar technology. Solely owned the entire development, from dataset acquisition and machine learning model design through hardware implementation (PCB design, firmware development, signal processing algorithms) to end-user Android application with Bluetooth-LE communication.

Radar-Based Vital Sign Monitoring, Research Project
2021
Contributed to the development of a radar-based system for contactless heart rate and respiration rate monitoring, including sensor characterization, algorithm development, dataset acquisition and scientific assessment of the performance (with ECG ground truth).

Optical Flow for Drones on PULP, Semester Thesis
2020
During the Thesis, I ported the driver for an Optical Flow Sensor (PMW3901, PixArt) from the STM32 to a PULP chip. The sensor aids the stabilization of a Crazyflie drone and has been used in a PULP-based nano-UAV.

Federated Learning on PULP, Course Project
2020
Developed from scratch a CNN model, with support for both forward and backward propagation for learning. The implementation, written in C, was designed for efficient parallelization on an 8-core open-source hardware platform, and has served as a starting point for further development.

Deep Convolutional Networks on STM32, Course Project
2020
Developed and evaluated different techniques to port a Keras neural network on the STM32, focusing on the efficiency and accuracy tradeoff between a full-precision and a quantized version.

Computer Skills

Python, C, C++, Linux, Git, Tensorflow, Keras
Advanced
Bash, LaTeX, PyTorch, Rust
Intermediate
HTML, CSS, VHDL, Verilog, PHP
Basic

Languages

Italian, English
Proficient
German
A2