I am a postdoctoral researcher at EPFL, working with the LTS2 and LPDI laboratories.
I will soon be a research scientist at Isomorphic Labs.

I research graph neural networks and their applications to dynamical systems and computational biology, specifically for protein and drug design. I am also the creator of Spektral, a library for graph deep learning in TensorFlow/Keras.

I obtained my PhD at the Swiss AI Lab IDSIA. I hold an MSc in Computer Science and Engineering with honors from Politecnico di Milano.

In my free time, I co-host and manage Smarter Podcast, a live-streaming podcast in Italian in which we interview AI researchers from academia and industry.


I'm thrilled to announce that I will be joining Isomorphic Labs (London, UK) to help reimagine the drug discovery process using AI. Exciting times ahead!

Our paper "Generalised implicit neural representations" has been accepted at NeurIPS 2022.

I will be Publicity Chair for the IEEE International Workshop on Machine Learning for Signal Processing (2023).

I had the absolute pleasure of chatting about cellular automata, emergence, life, graphs, and much more with the amazing Tim and Keith of Machine Learning Street Talk!

In collaboration with part of the team that I mentored at LOGML 2021, we have released a preprint on unsupervised embedding of heterophilous graphs.

I have become a member of the ELLIS Society, one of the leading non-profit organizations for promoting European AI.

I am co-organizing a special session on Deep Learning for Graphs (DL4G) at WCCI 2022. Read the call for papers here.

I have successfully defended my PhD dissertation!

Our paper "Learning graph cellular automata" will appear at NeurIPS 2021.

Our paper "Understanding pooling in graph neural networks" is out on arXiv.

The paper from my collaboration with Menten AI, "XENet: using a new graph convolution to accelerate the timeline for protein design on quantum computers", was published in PLOS Computational Biology.