About Me

I am a Ph.D. student at the Graph Machine Learning Group, within the Swiss AI lab IDSIA, at Università della Svizzera italiana (USI), under the supervision of Prof. Cesare Alippi. I obtained BSc (2017) and MSc (2020) degrees in Computer Science and Engineering at Politecnico di Milano. My master thesis project has been supervised by Prof. Nicola Gatti.

What I'm Doing

My research focuses on problems regarding irregular time series on irregular structures, like prediction imputation control over sensor networks manifolds.

You can find a list of my publications here.

Spatio-temporal data processing

My studies focus on analysis of multivariate time series, like sensor network streams.

Graph Neural Networks

I study deep learning solutions, with a particular focus on GNNs.

Data Challenges

I'm interested in data-related issues, like dealing with missing values and irregularities in the data stream.

Real-world applications

I love to see how developed scientific methods can be game-changers in real-world cases (see industry projects section).

Open Source Projects

I strongly believe in the worldwide accessibility of science. As such, I make the software I develop for my research publicly available (whenever possible) through my GitHub page. You can also find the code related to my publications on the GitHub page of Graph Machine Learning Group.

We recently released a library on Spatiotemporal Graph Neural Networks!

Torch Spatiotemporal

Torch Spatiotemporal (TSL) is a library built upon PyTorch and PyG for neural spatiotemporal data processing, with a focus on Graph Neural Networks.

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