Scholar
Luca Costabello
Google Scholar ID: O1Blx4AAAAAJ
Accenture Labs
Citations & Impact
Citations
1,100
H-index
18
i10-index
21
Publications
20
Co-authors
0
Resume (English only)
Academic Achievements
- AmpliGraph: A Python library for Representation Learning on Knowledge Graphs, won the Best Technical Advance In The Field Of Data Science/AI From A Research Organisation at the 2019 European DatSci & AI Awards!
- CLARIFY (EU-funded Horizon 2020 project): Leading Accenture activities in the project, building interpretable, graph-based decision support systems for stratification of oncology patients based on post-treatment complication risks.
- ECAI 2020 Tutorial: Overview of Knowledge Graph Embeddings from a theoretical and applicative standpoint, including live hands-on session.
- AAAI 2019 Tutorial: Snapshot of XAI to date, with a focus on machine learning and symbolic AI, XAI in real-world and large-scale applications, state-of-the-art techniques and best practices.
- PRISSMA: A context-aware presentation layer for Linked Data that selects the most appropriate RDF presentation according to mobile context, using graph edit distance to compute error-tolerant subgraph isomorphisms between context graphs.
- Shi3ld: An access control (authorization) module for triple stores, protecting SPARQL queries and HTTP operations on Linked Data.
- Linked Data Spam Dataset: An annotated RDF dataset polluted by synthetic malicious triples, useful to train and test Linked Data spam filters.
Background
- Research Scientist and Engineer, focusing on knowledge graphs applications, machine learning for graphs, and explainable AI. Formerly at Fujitsu, Inria, and Telecom Italia.
Miscellany
- Languages: English (Proficient), French (Professional), Italian (Native).
Co-authors