Outreach
Talks, panels, community work, and research mentoring.
Talks
Invited talks and presentations at academic seminars, workshops, and industry events.2023
| Nov 22 | A Primer on Graph Neural Networks COLT Seminar, University of Pompeu Fabra, Barcelona |
| Sep 14 | Edge Directionality Improves Learning on Heterophilic Graphs Temporal Graph Reading Group |
| Sep 07 | Edge Directionality Improves Learning on Heterophilic Graphs Explainability and Applicability of GNNs Workshop, Kassel |
2022
| Sep 28 | Improving Machine Learning at Twitter using Graphs Privacy Week |
| Sep 09 | Learning on Graphs with Missing Node Features TigerGraph Reading Group |
| Mar 01 | Learning on Graphs with Missing Node Features Learning on Graphs and Geometry Reading Group |
| Feb 24 | Learning on Graphs with Missing Node Features Machine Learning Research Group, University of Oxford |
2021
| Nov 23 | Learning on Graphs with Missing Node Features University of Cambridge AI Research Group Talks |
| Nov 17 | Graph Neural Networks with Almost No Features Toronto Machine Learning Summit |
| Jun 16 | Machine Learning on Dynamic Graphs: Temporal Graph Networks MLOps World 2021 |
| Apr 26 | Machine Learning on Dynamic Graphs: Temporal Graph Networks Intel ML Seminar |
| Apr 09 | Machine Learning on Dynamic Graphs: Temporal Graph Networks GNNSys'21 Workshop |
| Jan 22 | Dynamic Graphs and Temporal Graph Networks University of Liverpool Networks and Distributed Computing Series |
2020
Conversations
| 2021/03/02 | Scaling Graph Neural Networks to Twitter-scale with Zak Jost |
| 2021/01/14 | My journey, my research at Twitter and Imperial College, and my work at LeadTheFuture with The Smarter Podcast |
Workshop Involvement
| 2023/12 | Temporal Graph Learning Workshop | NeurIPS 2023 | Organizer |
| 2022/12 | Temporal Graph Learning Workshop | NeurIPS 2022 | Panel |
| 2022/12 | NeurReps Workshop – Symmetry and Geometry in Neural Representations | NeurIPS 2022 | PC Member |
| 2022/02 | GCLR 22 – 2nd Workshop on Graphs and more complex structures for learning and reasoning | AAAI 2022 | PC Member |
| 2021/10 | GReS – Workshop on Graph Neural Networks for Recommendation and Search | ACM RecSys 2021 | PC Member |
| 2021/04 | GNNSys'21 – Workshop on Graph Neural Networks and Systems | MLSys 2021 | PC Member |
| 2021/02 | AAAI-21 GCLR | AAAI 2021 | PC Member |
Supervision and Mentoring
Mentoring bright and motivated students is one of the most rewarding aspects of my research. I am grateful for their creativity and curiosity, and for how much I learn from them in return.
Below are the students I have had the pleasure to supervise. If you are a prospective student interested in working with me, feel free to contact my former mentees to learn more about my mentoring style and what collaboration with me looks like.| 2025/05 — Present | Davide Marincione — PhD Student @ Sapienza University of Rome Model Merging Improves Zero-Shot Generalization in Bioacoustic Foundation Models |
| 2024/10 — Present | Simone Antonelli — ML Research Intern @ Amboss Technologies Predicting Link Closure in the Lightning Network with Temporal Graph Networks (Work in Progress) |
| 2024/10 — 2025/04 | Marco Pegoraro — ML Research Intern @ VantAI Neo 1: a unified model for all-atom structure prediction and generation of all biomolecules |
| 2024/08 — Present | Harrison Rush — ML Engineer @ Amboss Technologies MP-Flow: A Deep Graph Reinforcement Learning Agent for Maximizing Throughput in the Lightning Network (Under Review) |
| 2024/03 — 2025/04 | Thomas Castiglione — ML Researcher @ VantAI Neo 1: a unified model for all-atom structure prediction and generation of all biomolecules |
| 2024/03 — 2025/04 | Andy Huang — PhD Student @ Mila TGB: Temporal Graph Benchmark for Machine Learning on Temporal Graphs UTG: Towards a Unified View of Snapshot and Event Based Models for Temporal Graphs |
| 2023/11 — 2024/05 | Vincent Davis — ML Engineer @ Amboss Technologies Channel Balance Interpolation in the Lightning Network via Machine Learning |