Nicola De Cao
Research Scientist at Google DeepMind
Stony Stratford, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolNicola De Cao is a research scientist specializing in machine reading comprehension and broader NLP for natural language understanding, currently at Google DeepMind after research roles at Google, Hugging Face and Facebook AI. With a PhD from the University of Amsterdam and visiting ties to EdinburghNLP, he blends (semi-)supervised and unsupervised deep learning with reasoning and reinforcement methods to push QA and NLU frontiers. Over a decade of experience includes applied research at major AI labs and concrete open-source impact—contributions to the widely used AllenNLP library (dataset readers, tests and bug fixes) show his attention to reproducible research tooling. He pairs rigorous academic credentials (cum laude degrees) with hands-on engineering across industry and research, often focusing on the less obvious bridge between model reasoning and practical dataset engineering.
10 years of coding experience
2 years of employment as a software developer
Bachelor’s Degree, Computer Science, 110/110 cum Laude, Bachelor’s Degree, Computer Science, 110/110 cum Laude at Università degli Studi di PadovaDoctor of Philosophy - PhD, Machine Learning and Natural Language Processing, Doctor of Philosophy - PhD, Machine Learning and Natural Language Processing at The University of EdinburghMaster’s Degree, Artificial Intelligence, 9.1 cum Laude, Master’s Degree, Artificial Intelligence, 9.1 cum Laude at University of Amsterdam
Italian, English
Stackoverflow
1reputation
0reached
1answer
0questions
Github Skills (7)
pytorch10
nlp10
python10
natural-language-processing10
data-science10
testing9
java6
Programming languages (7)
Github contributions (5)
allenai/allennlp
Dec 2018 - May 2020
An open-source NLP research library, built on PyTorch.
Role in this project:
ML Engineer
ML EngineerContributions:7 commits, 9 PRs, 24 comments in 1 year 5 months
Contributions summary:Nicola primarily contributed to the AllenNLP library by implementing and modifying dataset readers, specifically for bAbI and Qangaroo tasks. They added new dataset readers, incorporating necessary code changes, tests, and type corrections. Furthermore, the user addressed bug fixes and made documentation improvements, demonstrating a focus on refining NLP-related components within the project.
nlppytorchtransformerspythonbert
nicola-decao/efficient-autoregressive-EL
May 2021 - May 2022
Pytorch implementation of Highly Parallel Autoregressive Entity Linking with Discriminative Correction
Contributions:19 commits, 17 pushes, 1 branch in 11 months
nlppytorchparallelentityentity-linking
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.