Mattia Stighezza

About

Mattia Stighezza (Member, IEEE), received the B.Sc. and M.Sc. degrees in electronic engineering in 2017 and 2020 respectively, and the PhD degree in Information Technologies in 2024 from the University of Parma, Parma, Italy. His current research interests include the design of embedded systems in the field of electrochemical analysis and lithium-ion batteries.

Work

University of Parma

|

Technologist METROFOOD-IT project

Italy

→

Education

University of Parma

Italy
→
PhD

University of Parma

Italy
→
MD Electronic Engineering

Publications

Machine Learning-Enhanced Flexible IL-6 Sensor for Rapid Threshold Detection

IEEE Sensors Journal

journal-article

A Flexible Multichannel Platform for Versatile E-Nose and E-Tongue Operations

IEEE Transactions on Instrumentation and Measurement

journal-article

Evaluation of a Voltametric E-Tongue Combined with Data Preprocessing for Fast and Effective Machine Learning-Based Classification of Tomato Purées by Cultivar

Sensors

journal-article

Evaluation of a Voltametric E-Tongue Combined with Data Preprocessing for Fast and Effective Machine Learning-Based Classification of Tomato Purées by Cultivar

Sensors

journal-article

Machine learning and impedance spectroscopy for battery state of charge evaluation

2023 IEEE International Workshop on Metrology for Automotive (MetroAutomotive)

conference-paper

An Improved Method Based on Support Vector Regression With Application Independent Training for State of Charge Estimation

IEEE Transactions on Instrumentation and Measurement

journal-article

A flexible machine learning based framework for state of charge evaluation

2022 IEEE International Workshop on Metrology for Automotive (MetroAutomotive)

conference-paper

FPGA Implementation of an Ant Colony Optimization Based SVM Algorithm for State of Charge Estimation in Li-Ion Batteries

Energies

journal-article

FPGA Implementation of an Ant Colony Optimization Based SVM Algorithm for State of Charge Estimation in Li-Ion Batteries

Energies

journal-article

HDL Code Generation from SIMULINK Environment for Li-Ion Cells State of Charge and Parameter Estimation

Lecture Notes in Electrical Engineering

book-chapter