Machine Learning Journal Club APS - University of Turin

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Latest News

  • MLJC members invited to the Uniwersytet Mikołaja Kopernika w Toruniu for the THUS 2021
    It was our pleasure to have been invited to the Uniwersytet Mikołaja Kopernika w Toruniu for the THUS 2021 – Torun Humanities and Social Sciences Summer Program. The group of the Machine Learning Journal Club composed by Pietro Sillano Beatrice Villata Simone Poetto Arianna Di Bernardo, worked on the project “Machine […]
  • MLJC starts new project on Realtime Scientific Machine Learning
    We are now ready for the next stage: our new projects on #BCIs and Realtime Scientific Machine Learning (by exploiting Xilinx‘s #FPGAs + NVIDIA Jetson Xavier) can finally take place. Further updates are coming on our website ( as well as a more detailed prospectus. The MLJC would like to express […]
  • Machine Learning Journal Club selected in the EO Dashboard Hackathon by ESA, NASA, JAXA
    We are glad to announce that the Machine Learning Journal Club team, composed by Beatrice Villata Andrea Semeraro Luca Pezzini Micol Olocco and Luca Bottero , has been selected as one of the finalist competitors in the EO Dashboard Hackathon (, organized by NASA – National Aeronautics and Space Administration, European […]
  • The Scientific Machine Learning team from MLJC presents at JuliaCon 2021
    It’s been an honour for our Scientific Machine Learning team (Luca Bottero, Valerio Pagliarino, Simone Azeglio, Francesco Calisto) to give a lighting talk at JuliaCon 2021. It is about a real world test of the Julia #SciML ecosystem, using #NeuralPDE.jl in particular.You can take a look at it on the Julia […]
  • MLJC gets on the Neurohackathor 2021 podium
    On 23rd and 24th May 2021 the Medical AI and BCI team from Machine Learning Journal Club participated in the NeuroHackathor 2021, hosted by the Neurotechnology Scientific Student Club from Torùn, Poland. NeuroHackathor 2021 is an international hackaton for studying engineers, programmists, cognitive scientists and others interested in neurotechnology and human daily […]
  • Politecnico di Torino on MLJC results at BCI Hackathon
  • MLJC team tops hackathon podium

MLJC is Co-Host of Virtual BR41N.IO Hackathon – Spring School 2021


April 12-21, 2021


+3000 brain enthusiast



The Machine Learning Journal Club is honoured to be Co-Host of the Virtual Br41n Hackathon, organised by g.tec medical engineering in partnership with IEEE Brain.

The event will be held between the 17th and 18th of April 2021, as part of the BCI and Neurotechnology Spring School. MLJC will attend with five teams. We will have the opportunity to present our work and our association in front of an international audience.

All the results will be available open-source on our GitHub.

Brain Hackathon

BR41N.IO is a two days event designed to be a learning experience for developers, students, scientists and engineers who cram and build Brain Computer Interface (BCI) applications.

Spring School

A 10 days learning experince with Neurotechnology experts from all over the world. The members from MLJC are taking part to the Spring School organized by g.tec.

Our winning team

Our Teams

TOP-ECoG Hand Pose

Arianna Di Bernardo
Gabriele Penna
Simone Azeglio
Simone Poetto

Stroke Rehab Motor Imagery

Eleonora Misino
Lorenzo Migliori
Beatrice Villata
Pietro Sillano

P300-speller 1

Aurora Micheli
Flavio Sartori
Ilaria Gesmundo
Luca Bottero

P300-speller 2

Enrico Sansone
Pietro De Luca
Sara Giganti
Tanisha Khan

Syntetic SSVEP

Elios Ghinato
Giacomo D'Amicantonio
Pio Raffaele Fina
Marco Bottino
Vincenzo Triglione

Our teams at work

About us

We are a group of students from the University of Turin and the Polytechnic University of Turin, mostly from a STEM background.

We are passionate about machine learning and artificial intelligence, thus we created a community where to share our geeky ideas and our expertise.

We are actively engaged in research projects with a broad, interdisciplinary focus and participating in hackathons / competitions related to AI.

If you’re interested in taking part in any way in our research projects or learning activities, feel free to drop an email at: info(at)

What we do

The aim of our association is to promote hands-on knowledge of machine learning and artificial intelligence across the academic and civic landscape of Turin.

We believe interdisciplinarity and cross-contamination can be the key to new discoveries and fruitful, engaging ideas.

We try to innovate learning and research paradigms with a focus on self-organization and peer-learning / peer-reviewing, ultimately producing industry-grade science.

In order to promote machine learning literacy we jump-started a wide set of projects, on various premises and online:

  • We took over the University of Turin after-hours, delivering free-for-all courses on Python for machine learning
  • We engaged our more experienced members in open and horizontal research projects on natural language processing, theoretical machine learning and medical machine learning
  • We encouraged and financed the participation of our members to hackathons and competitions
  • We published divulgatory articles on machine learning techniques and hot topics

Our Story

We started our first activities as a little group of students from the M.Sc. in Physics of Complex Systems at the University of Turin.
We were curious about emergent possibilities stemming from Data Mining, Machine Learning and Artificial Intelligence: that’s why we started experimenting with real-world projects and participating in some Kaggle competitions we were passionate about (for example, we took part in the Deep Fake Detection Challenge).

Going forward, we decided to open our group to students from different backgrounds: in order to build some common knowledge, we started organizing extra-curricular lessons and activities, covering Python applied to machine learning (you can find the course material here).

As we meet and engage with new people from all walks of science, our community grows large and diverse: we are proud to count members from computer science, engineering, mathematics, biology, economics and neuropsychology to name a few.

We meet regularly (online or in person), to work and organize projects related to Machine Learning and its applications. You can find more information about our projects here.


MLJC presented “Physics Informed Machine Learning Simulator for Wildfire Propagation” at AAAI Symposium 2021

MLJC presented the following research at AAAI-MLPS Symposium 2021 on February 2021. Please find the proceedings below or in the official website:

The aim of this work is to evaluate the feasibility of re-implementing some key parts of the widely used Weather Research and Forecasting WRF-SFIRE simulator by replacingits core differential equations numerical solvers with state-of-the-art physics-informed machine learning techniques tosolve ODEs and PDEs, in order to transform it into a real-time simulator for wildfire spread prediction. The main programming language used is Julia, a compiled language which offers better perfomance than interpreted ones, providing Justin Time (JIT) compilation with different optimization levels. Moreover, Julia is particularlywell suited for numerical computation and for the solution ofcomplex physical models, both considering the syntax and thepresence of specific libraries such as DifferentialEquations.jl and ModelingToolkit.jl.

Our toolbox