Sebastian Ruder
Research Scientist at Meta
Berlin, Germany
Summary
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Rockstar🎓
Top SchoolSebastian Ruder is a research scientist based in Berlin with over a decade of experience working at the intersection of NLP, machine learning, and deep learning, currently on research at Meta. He has led multilinguality efforts at Cohere and previously contributed to applied research at DeepMind and AYLIEN, where he built and scaled aspect- and entity-based sentiment systems across domains and languages. His open-source work ranges from adding a streaming BLEU metric to Google’s seq2seq and improving the XTREME cross-lingual benchmark to writing temporal and contextual reasoning rules for the OpenCog AGI framework. With a PhD in NLP and a demonstrated ability to convert research into production-ready tooling, he specializes in adapting models to low-resource languages by combining clever algorithms with novel data strategies.
12 years of coding experience
7 years of employment as a software developer
Bachelor's degree, Computational Linguistics, English Linguistics, 1.0 (German scale), i.e. A+, Bachelor's degree, Computational Linguistics, English Linguistics, 1.0 (German scale), i.e. A+ at Ruprecht-Karls-Universität Heidelberg / University of HeidelbergAbitur, Abitur at Clara-Schumann-Gymnasium LahrBachelor's degree, Computer Science and Language, Bachelor's degree, Computer Science and Language at Trinity College, DublinDoctor of Philosophy (Ph.D.), Natural language processing, Doctor of Philosophy (Ph.D.), Natural language processing at National University of Ireland, Galway
German, English, French, Spanish, Portuguese, Latin
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (20)
transformers10
python10
classification10
nltk10
machine-learning10
natural-language-understanding10
text-classification10
seq2seq10
classify10
tensorflow210
tensorflow10
natural-language-processing10
transformer10
nlp10
evaluation9
Programming languages (8)
Github contributions (5)
google-research/xtreme
Mar 2020 - Oct 2022
XTREME is a benchmark for the evaluation of the cross-lingual generalization ability of pre-trained multilingual models that covers 40 typologically diverse languages and includes nine tasks.
Role in this project:
ML Engineer
ML EngineerContributions:1 review, 26 commits, 10 PRs in 2 years 6 months
Contributions summary:Sebastian primarily focused on updating scripts and pre-processing steps related to the XTREME benchmark. They modified Python scripts, particularly those related to token classification tasks. The changes included adapting code for different model types, incorporating few-shot learning capabilities, and evaluating model performance, indicating a focus on improving the benchmark's functionality and evaluation metrics.
nlpdiverseninemultilingual-modelsbert
opencog/opencog
Mar 2014 - Aug 2014
A framework for integrated Artificial Intelligence & Artificial General Intelligence (AGI)
Role in this project:Back-end Developer
Back-end DeveloperContributions:224 commits in 5 months
Contributions summary:Sebastian primarily contributed to the development of rules and agents within the opencog/opencog repository. They added and modified rules, specifically focusing on creating, implementing, and refining rules related to the context and temporal reasoning components. These rules appear to be core to the project's goals of integrated artificial intelligence and artificial general intelligence. They also added a new example to illustrate the use case of the be-inheritance-rule
unsupervised-learning-algorithmsroboticsnatural-language-understandingartificial-general-intelligenceintegrated
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