Fondamenti di Programmazione e Laboratorio

Starting from next week, I will work as Lab assistant at the Fondamenti di Programmazione e Laboratorio course of the bachelor’s degree in mathematics.

Paper Accepted at SMC2020

Finally a good news in these difficult times!
I’m proud to announce that our paper “ROS-Neuro Integration of Deep Convolutional Autoencoders for EEG Signal Compression in Real-time BCIs” has been accepted at the 2020 IEEE International Conference on Systems, Man, and Cybernetics. I thank my co-authors for their work and support.

In the paper, we use a convolutional autoencoder to compress EEG signals, and deploy the trained model inside a ROS-Neuro node, in order to allow for an efficient real-time processing of the input data. This can be a first step towards many interesting BCI applications, such as the remote control of machine, with only the power of tought! So cool!

Update: the paper is now avaialable on the arXiv here: arXiv:2008.13485

Internship at Camlin Ltd.

In the next few months I will be working as an intern at Camlin Italy, based in Parma. I will apply Machine Learning techniques to Brain Computer Interfaces.
I’m excited to start this new adventure, let’s see what the future will bring!

MusAE paper accepted at ECAI2020

Great news!
My paper on MusAE, a generative model for music editing and generation, has been officially accepted at the 24th European Conference on Artificial Intelligence. I thank my co-authors Antonio Carta and Davide Bacciu for their work and support. I look forward to present this work next June in the suggestive location of Santiago de Compostela.

Here you can find a link to some additional material, comprising of generated songs and interpolations. You can also find the full paper on ArXiv.

Electoral Results

Good news!
Elections results are now official: Andrea Lisi and I have been elected as students’ representatives of the PhD council.

Thanks to everyone who voted for me, I promise to commit myself to my new role!

MusAE’s source code on Github

The source code of my latest project, MusAE, is now available on Github. If you’re interested, go check it out! I already spoke (in broad terms) about MusAE in a previous post, the technical details will be available soon.

(Spoiler) You can already read about the details of an early version of MusAE in my Master’s thesis.


Upcoming elections

I decided to run for the position of students’ representative in the PhD council in the upcoming elections, on the 27th of November.

May the best man win!

PRIN – Multicriteria Data Structures

I’ve been selected to participate to a new project, funded by the Italian Ministry of Education, and organized by a pool of Italian universities spread all over the country.
This project proposes to integrate traditional data structures with new, “learned” data structures, that are trained to better fit the input data.
It seems an interesting, and yet not much explored, area of application for machine learning!

If you want to know more, feel free to check the project’s website, where you can find more detailed information.

MusÆ – Audio samples available on YouTube

At the following link, you can find a few audio samples generated by MusAE, the Machine Learning model for MIDI music manipulation I am currently working on. The name is an acronym of Music Adversarial autoEncoder, and a tribute to ancient Greek’s goddess of sciences and arts. The link redirects you to a YouTube playlist containing both song reconstructions (MusAE is based on an autoencoder model) and interpolations between two different measures. There is also a medley between Michael Jackson’s “Billie Jean” and Pink Floyd’s “Brain Damage”, which combines the reconstruction and interpolation capabilities of the model.

MusAE’s main goal is to assist new artists (even with limited knowledge of music theory) in creating their new masterpieces by automatically modifying relevant properties of musical pieces, thus leaving the artists free to concentrate only on the creative aspects of music composition, without caring too much about low-level technical nuisances.
This work is just at its initial stages, but I think the result are already quite impressive!

If you’re interested in MusAE, more technical details will be coming soon.

Hello World!

This is my first post of my personal web page.
Here I am going to post updates about my PhD life, my research  and activities.
Stay tuned!