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)mljc.it
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 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.
The Machine Learning Journal Club participated in the SHARPER – European Researchers’ Night in Turin on September 24th 2021, organized by the University of Turin and Politecnico of Turin, in the beautiful frame of the Castello del Valentino. The title of the stand was “MACHINE LEARNING E L’INTELLIGENZA ARTIFICIALE DEL FUTURO”. At our stand we presented projects spacing from Brain Computer Interfaces to Scientific Machine Learning.
The MedicAI team showcased the new BCI hardware from OpenBCI that will allow the team to run custom experiments in order to acquire data for training, validation and testing of new advanced algorithms for EEG signal classification. These last are fundamental for critical applications, for example in allowing communication or the use of computers for people that cannot use their hands because of diseases. [Open the page]
We presented an overview on our past Scientific Machine Learning projects that have the goal to create accurate and efficient models of natural phenomena by merging the knowledge coming from the physics-based approaches using differential equations and the data-driven approaches. In particular we showcased the work “Physics-Informed Machine Learning Simulator for Wildfire Propagation” and our contribution to “NeuralPDE: Automating Physics-Informed Neural Networks (PINNs) with Error Approximations” [Open the page]
We presented an electronics based on a SoC with GPU acceleration , an FPGA and a large amount of inputs and outputs that allows to run machine learning algorithsm not only “offline” on dataset already saved on the hard drive, but also in real time on data coming from sensors. In this way it is possible to deploy machine learning applications where it is required by the model to trigger decisions with a very low latency (thanks to the FPGA-based neural network inference). In this project the final goal is the realization of adaptive control for dynamical systems that can merge knowledge coming from physics priors and sensor fusion. This project is still “work in progress”! [Open the page]
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.