Alexander Fabbri
Research Scientist at Meta
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolAlexander Fabbri is a research scientist focused on alignment and large-model evaluation, currently working at Meta Superintelligence Labs after roles at Scale AI and Salesforce. With a PhD from Yale and 11 years in NLP and ML, he has led work on multilingual reasoning evaluation, coding data specification, long-context summarization, and factual consistency. He bridges academic rigor and product-driven data practices—designing annotation specs, collaborating with frontier labs, and ensuring high-quality training data. His background includes applied internships at AWS and Facebook AI and early research in sarcasm and sentiment, reflecting a blend of core NLP research and real-world system building. Based in New York, he brings deep experience in both evaluation methodology and data-centric engineering for safety-focused ML research.
11 years of coding experience
5 years of employment as a software developer
Computer Science French, Computer Science French at Columbia University in Paris at Reid Hall and Université Denis Diderot (Paris VII)High School, High School at Chaminade High SchoolDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Yale UniversityBachelor's Degree Data Science (Previously called Computer Science-Statistics) Major, Bachelor's Degree Data Science (Previously called Computer Science-Statistics) Major at Columbia University
English, Polish, French
Github Skills (45)
pytorch10
summarization10
artificial-intelligence10
python10
multi-document10
machine-learning10
multimodal10
ml10
datasets10
llm10
audio10
deep-learning10
tensorflow10
deep-neural-networks10
natural-language-processing10
Programming languages (7)
Github contributions (5)
Alex-Fabbri/Multi-News
Jun 2019 - May 2023
Large-scale multi-document summarization dataset and code
Contributions:1 PR, 28 pushes, 43 comments in 3 years 11 months
multi-documentsummarizationmulti-newsmulti-document-summarization
Yale-LILY/SummEval
Aug 2020 - Nov 2022
Resources for the "SummEval: Re-evaluating Summarization Evaluation" paper
Contributions:1 review, 11 commits, 6 PRs in 2 years 3 months
nlpnatural-language-processingevaluationsummarization
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