I’m happy to announce that our latest paper has been accepted for publication in MDPI Bioengineering!
In
this work we implemented a deep neural architecture for the efficient
processing of EEG data, aiming at the recognition of users’ motion
intentions of the upper limbs.
I thank my co-authors Michele Barsotti, Luca Ascari and Davide Bacciu for their work and support. Thanks for the wonderful experience!
Feel free to check out the paper at the following link:
On Thursday 03/11/2020 there will be the first day of the event Visions of Tomorrow. It consists in a series of talks, given by either industry or academic experts, about the future directions of their respective fields of expertise.
Despite the event is mainly intended for PhD students and last-year Master’s students, it is open to everyone!
I will have the pleasure to be the session chair of the first two talks: Dr. Marco Calderisi and Dr. Luca Ascari. Looking forward to it!
If you want to know more about the event, you can check out the official website here.
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.
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
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!
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.
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!
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.
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!
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.
