Andrea Cossu is an Assistant Professor and Data Science PhD whose decade-long career blends academic research and R&D leadership focused on Continual Learning and recurrent neural networks for sequential data. Based in Tuscany, he transitioned from a Google Brain research internship and a PhD at Scuola Normale Superiore to postdoctoral work and a faculty role at Università di Pisa while also directing R&D at KlinK Srl. His work spans Network Analysis and Agent-Based Modeling to study emergent phenomena, bringing computational rigor to complex systems beyond standard supervised learning. Andrea is experienced in moving ideas from theory to application, often targeting real-world sequential problems where continual adaptation matters. He combines deep theoretical knowledge with hands-on product-minded engineering, making him effective at bridging research and deployed solutions. A subtle strength is his sustained dual track of academic publication and industrial R&D, which keeps his methods both innovative and practically grounded.
10 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Data Science, Doctor of Philosophy - PhD, Data Science at Scuola Normale Superiore
Master degree, Artificial Intelligence, Master degree, Artificial Intelligence at Università di Pisa
Implementation of Relation Network and Recurrent Relational Network using PyTorch v1.3. Original papers: (RN) https://arxiv.org/abs/1706.01427 (RRN): https://arxiv.org/abs/1711.08028
Contributions:233 commits, 3 PRs, 197 pushes in 2 years 6 months
pytorchrelationalpythonarxivabs
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