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Francesco Grassi

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Related publications (9)

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We present a new method for electrochemical sensing, which compensates the fouling effect of propofol through machine learning (ML) model. Direct and continuous monitoring of propofol is crucial in the development of automatic systems for control of drug i ...

2020

Tensor Robust Pca On Graphs

Pierre Vandergheynst, Nauman Shahid, Francesco Grassi

We propose a graph signal processing framework to overcome the computational burden of Tensor Robust PCA (TRPCA). Our framework also serves as a convex alternative to graph regularized tensor factorization methods. Our method is based on projecting a tenso ...

IEEE2019

Live Demonstration: Quasi-Digital Portable Pen to Monitor Anaesthetics Delivery

Sandro Carrara, Danilo Demarchi, Simone Aiassa, Francesco Grassi

The live demonstration presents the innovative concept of a portable pen-device able to sense anaesthetic compounds over time for improved anaesthesiology practice. A custom Printed Circuit Board (PCB) manage in the event-based quasi-digital domain the sam ...

IEEE2019

A Time-Vertex Signal Processing Framework

Nathanaël Perraudin, Benjamin Ricaud, Andreas Loukas, Francesco Grassi

An emerging way to deal with high-dimensional non-euclidean data is to assume that the underlying structure can be captured by a graph. Recently, ideas have begun to emerge related to the analysis of time-varying graph signals. This work aims to elevate th ...

Institute of Electrical and Electronics Engineers2018

Towards Stationary Time-Vertex Signal Processing

Pierre Vandergheynst, Nathanaël Perraudin, Andreas Loukas, Francesco Grassi

Graph-based methods for signal processing have shown promise for the analysis of data exhibiting irregular structure, such as those found in social, transportation, and sensor networks. Yet, though these systems are often dynamic, state-of-the-art methods ...

Ieee2017

Multilinear Low-Rank Tensors on Graphs & Applications

Pierre Vandergheynst, Nauman Shahid, Francesco Grassi

We propose a new framework for the analysis of low- rank tensors which lies at the intersection of spectral graph theory and signal processing. As a first step, we present a new graph based low-rank decomposition which approximates the classical low-rank S ...

2016

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2016

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Graph Signal Processing generalizes classical signal processing to signal or data indexed by the vertices of a weighted graph. So far, the research efforts have been focused on static graph signals. However numerous applications involve graph signals evolv ...

2016

Biocompatible Packagings for Fully Implantable Multi-Panel Devices for Remote Monitoring of Metabolism

Giovanni De Micheli, Sandro Carrara, Andrea Cavallini, Camilla Baj-Rossi, Francesco Grassi

This paper compares three different biocompatible packagings suitable to support full implantation of multi-panel sensors for remote monitoring of metabolism. The three packagings have been designed, realized and implanted in mice for 30 days. ATP and neut ...

2015