Timeline

2024/1
 Quite an update: I have just started as a Postdoctoral Fellow researcher at Technion (Israel), where I will work with Prof. Haggai Maron on Equivariance, Expressiveness, Graph Neural Networks, Geometric Deep Learning and friends :)

2023/11
 Big news: I have just discussed my PhD thesis with examiners Prof. Ben Glocker and Prof. Yaron Lipman. I am excited to share I have passed the viva examination without corrections, this marking the (successful) end of my PhD journey :D

2023/8
 It's been a while, huh? ... Well, these past months I've been mostly working on my PhD thesis 'Expressive and Efficient Graph Neural Networks'. I am happy to share that I have finally submitted it!

2023/5
 New preprint out: Edge Directionality Improves Learning on Heterophilic Graphs. We study how to handle directed graphs in a principled manner (and what are the theoretical and practical benefits of the approach, especially in heterophilic settings).

2023/4
 Our paper Graph Positional Encoding via Random Feature Propagation has been accepted to ICML 2023!

2023/3
 I had the honour to give a talk as the penultimate lecture of the Geometric Deep Learning course at Oxford University. A great experience with a lot of interesting questions from the students :)

2023/1
 Our paper Graph Neural Networks for Link Prediction with Subgraph Sketching has been accepted at ICLR 2023 as a notable, top 5% paper!

2023/1
 The video of our tutorial 'Exploring the practical and theoretical landscape of expressive Graph Neural Networks' is available on youtube :)

2022/12
 Just held our tutorial at the Learning on Graph conference. Amazing experience with a lot of emerging interesting discussions!

2022/12
 I have been selected as one of the twenty best reviewers at the first edition of the Learning on Graph conference! I have also gathered some reflections and unsolicited thoughts in a short presentation I held during the opening remarks, take a look :)

2022/10
 Our tutorial proposal got accepted at Learning on Graph 2022! The tutorial will focus on the expressive power of Graph Neural Networks and I will present along with Beatrice Bevilacqua and Dr. Haggai Maron.

2022/10
 Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries got selected as oral presentation at NeurIPS 2022!

2022/9
 Our new paper Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries is accepted at NeurIPS 2022 – see you in New Orleans :)

2022/7
 I am honoured I will contribute to the Geometric Deep Learning AIMS 2022 course by holding a seminar on 'Subgraphs for more expressive GNNs'.

2022/7
 Exciting news – I got selected to join the LOGML 2022 summer school and I will work with Leonardo Cotta and Dr. Shubhendu Trivedi on 'Equivariant Poset Representations'.

2022/6
 New blogpost out! It covers the two works Cris Bodnar and I authored on 'Topological Message Passing'.

2022/6
 A new blogpost from Airbnb explains how they chose our SIGN model to suit their graph learning needs at scale.

2022/3
 Just given a talk at the Dagstuhl Seminar 'Graph Embeddings: Theory meets Practice'. I presented '(Graph) Representation Learning on Simplicial and Cellular Complexes' and spent three days with amazing researchers.

2022/3
 A new interview by Zak Jost just out. It covers our recent paper 'Equivariant Subgraph Aggregation Networks.

2022/1
 Our paper 'Equivariant Subgraph Aggregation Networks' has been accepted at ICLR 2022 as a spotlight!

2021/12
 I've just presented 'Subgraphs for more expressive GNNs' at the 2021 Nepal Winter School. Honoured!

2021/12
 New co-authored blogpost out: 'Using Subgraphs for More Expressive GNNs'. Gist: we gather together with M. M. Bronstein, C. Morris, L. Cotta, H. Maron and L. Zhao and discuss our related concurrent works together.

2021/11
 I am glad to share our paper 'Weisfeiler and Lehman Go Cellular: CW Networks' got accepted at NeurIPS 2021!

2021/10
 I had the pleasure to moderate the London ML Meetup on the latest works from Dr. Anees Kazi on GNNs for medical applications.

2021/9
 Excited to share I will spend October and November in Spain (València & Málaga). I will continue my research work remotely during this period :)

2021/8
 The code for simplicial and cellular message-passing which powers our latest approaches is out now!

2021/8
 I got selected to take part in the LOGML 2021 summer school! I will join Dr. Haggai Maron on exploring subgraphs for more expressive GNNs.

2021/7
 I managed to recognise my home town from the picture of a cup of espresso (!)'

2021/7
 Our latest paper on cellular message-passing was featured in a blogpost from Synced!

2021/6
 Just gave a talk with Cris Bodnar at TopoNets 2021 on our latest works on topological message-passing.

2021/6
 New pre-print out: 'Weisfeiler and Lehman Go Cellular: CW Networks'. We continue our exploration of message-passing on more general topological objects.

2021/6
 New post out on 'Provably expressive Graph Neural Network' on the Twitter Engineering blog :)

2021/5
 Cris Bodnar and I are presenting our paper 'Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks' at Cambridge's AI Research Talks :)

2021/5
 Our paper Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks' got accepted at ICML 2021!

2021/4
 I have presented 'Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks' along with Cris Bodnar and Yu Guang Wang at the MPI MIS + UCLA Math Machine Learning Seminar :)

2021/4
 Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks' got accepted as a spotlight at the GTRL ICLR 2021 workshop!

2021/3
 New pre-print out: 'Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks'. We explore generalisations of message-passing from graphs to simplicial complexes.

2020/10
 Happy to share I am starting (again) as a PhD candidate at Imperial College London under the supervision of Prof. Michael Bronstein. I will conduct my research activity part-time while working for Twitter.

2020/4
 New work on arXiv: 'SIGN: Scalable Inception Graph Neural Networks'. We propose a simple, yet effective approach to scale the computation of Graph Neural Networks to large-scale graphs.

2019/12
 I will be at NeurIPS 2019 in the following days to present our paper 'Learning Interpretable Disease Self-Representations for Drug Repositioning' at the NeurIPS 2019 Graph Representation Learning Workshop :)

2019/9
 New pre-print out: 'Learning Interpretable Disease Self-Representations for Drug Repositioning'. We train linear sparse self-encoding models for repurposing drugs.

2019/6
 Thrilled to announce Fabula AI is being acquired by Twitter and I will join on-board as a tweep Machine Learning Engineer!

2019/5
 I will spend one week in LA to attend the IPAM workshop 'Deep Geometric Learning of Big Data and Applications' – see you there :)

2018/10
 I am starting a PhD at USI (Università della Svizzera Italiana) advised by Prof. Bronstein. However, I will spend my first 4 months in London visting him at Imperial College London!

2018/6
 After graduating with distinction from Politecnico di Milano, I am happy to share that I have joined startup Fabula AI to explore applications of Geometric Deep Learning to Fake News Detection :)

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