This is a summary of my professional experience, including teaching, supervising students, and participating in the machine learning community.


Isomorphic Labs
Senior Research Scientist (2024 - Present), Research Scientist (2023 - 2024)
Isomorphic Labs is a digital biology company and sister company of Google DeepMind, on a mission to reimagine drug discovery with an AI-first approach and, ultimately, to model and understand the fundamental mechanisms of life.

École Polytechnique Fédérale De Lausanne (EPFL)
Postdoctoral Researcher (2022 - 2023)
At EPFL, I conducted research at the intersection of AI and structural biology, with a primary focus on applying neural fields and generative models to tackle the complex challenges of protein design.

Krembil Research Institute
Visiting Researcher (2019 - 2020)
The Krembil Institute is a world-leading neuroscience research organization based in Toronto. As a visiting researcher in the laboratory of Dr Taufik Valiante, I applied my research on geometric deep learning to the localization of epileptic seizures.



I have contributed to teaching, organizing, and supervising these university courses:

Faculty roles

I have been the Ph.D. representative for USI's Faculty of Informatics in 2018/2019.
During that time, I was the official point of contact between the Faculty and its Ph.D. students, participating in Faculty meetings and contributing to the strategical decisions of the university.


This is a list of my past and current roles as a member of the AI community:
  • Member of the ELLIS Society, one of the leading non-profit organizations for promoting European AI 🇪🇺
  • Publicity Chair for the IEEE International Workshop on Machine Learning for Signal Processing 2023.
  • Co-organizer of the special session on Deep Learning for Graphs (DL4G) at WCCI 2022.
  • Host of Smarter Podcast, a live-streaming podcast in Italian in which we interview AI researchers from academia and industry (2020-2021).


I am the main developer of Spektral, an open-source Python library for creating graph neural networks in TensorFlow and Keras. The project has thousands of active users and was one of the first libraries ever made for graph deep learning.

Supervising & Mentoring

SmoothPool: a Hierarchical Pooling Operator for GNNs
Y. Chen  |  Master's thesis (USI, 2022)

Exploring Implicit Neural Representations from a Signal Processing Perspective
J. Deschenaux  |  Semester project (EPFL, 2022)

Adaptive Neural Cellular Automata
A. Charneca  |  Semester project (EPFL, 2022)

Coarsening Disassortative Graphs
A. Bar, G. Gonzalez, A. Jamadandi, V. Polianskii, M. Thiessen, Z. Zhong  |  Student project (LOGML summer school, 2021)

Molecule Generation with Graph-based Generative Adversarial Networks
M. Nobile  |  Master's thesis (USI, 2021)

Prediction of Epileptic Seizures with Graph-based Deep Learning
A. Ruggeri  |  Master's thesis (USI, 2020)


Generalised Implicit Neural Representations
Neural Information Processing Systems (2022)  |  Slides 

Introduction to Graph Neural Networks and Graph Pooling
Graph Deep Learning course @ USI (Feb 28, 2022)  |  Slides 

Learning Graph Cellular Automata
Learning on Graphs and Geometry Reading Group (Jan 11, 2022)  |  Slides  Video 

Graph Neural Networks: Operators and Architectures
Dissertation defense @ USI (Dec 10, 2021)  |  Slides 

Pooling in Graph Neural Networks
Advanced Machine Learning course @ U. Manitoba (Dec 1, 2021)  |  Slides 

Learning Graph Cellular Automata
Italian Workshop on Machine Learning and Data Mining @ AIXIA (2021)  |  Slides 

Learning Graph Cellular Automata
Neural Information Processing Systems (Dec 7, 2021)  |  Slides 

Pooling in Graph Neural Networks
Graph Deep Learning course @ USI (Mar 15, 2021)  |  Slides 

Introduction to Graph Neural Networks
Graph Deep Learning course @ USI (Mar 1, 2021)  |  Slides 

Spectral Clustering with Graph Neural Networks for Graph Pooling
International Conference on Machine Learning (2020)  |  Slides 

Graph Neural Networks in Tensorflow and Keras with Spektral
Graph Representation Learning and Beyond @ ICML (2020)  |  Slides 

Graph Neural Networks e MinCut Pooling (in Italian)
Italian Association for Machine Learning (ML/DS Meetup) (2020)  |  Slides  Video 

Generative Adversarial Networks
Advanced Topics in Machine Learning course @ USI (Sep 17, 2020)  |  Slides 

Autoregressive Models for Sequences of Graphs
International Joint Conference on Neural Networks (2019)  |  Slides 


I have served as reviewer for these AI conferences, journals, and workshops:


  • Neural Information Processing Systems (NeurIPS)
  • International Conference on Learning Representations (ICLR)
  • International Conference on Machine Learning (ICML)
  • Computer Vision and Pattern Recognition (CVPR)
  • Learning on Graphs Conference (LoG)
  • The Web Conference (WWW)
  • International Joint Conference on Artificial Intelligence (IJCAI)
  • International Joint Conference on Neural Networks (IJCNN)
  • European Symposium on Artificial Neural Networks (ESANN)
  • International Conference on Acoustics, Speech, & Signal Processing (ICASSP)


  • Journal of Machine Learning Research (JMLR)
  • Transactions on Machine Learning Research (TMLR)
  • Transactions on Neural Networks and Learning Systems (TNNLS)
  • Applied Soft Computing (ASOC)
  • Neurocomputing
  • Transactions on Knowledge Discovery from Data (TKDD)
  • Transactions on Emerging Topics in Computational Intelligence (TETCI)
  • Transactions on Geoscience and Remote Sensing (TGRS)


  • New Frontiers in Graph Learning: Challenges, Perspectives, and Solutions (NeurIPS 2022)
  • Graph Neural Networks and Systems (MLSys 2021)
  • Graphs and more Complex structures for Learning and Reasoning (AAAI 2021, 2022)
  • ML Retrospectives (NeurIPS 2020)
  • Graph Representation Learning and Beyond (ICML 2020)
  • Graph Representation Learning (NeurIPS 2019)