--- title: "Greg S. Corrado — author profile and papers" description: "Greg S. Corrado, Google: 3 papers on Elamur Research (2013–2016), h-index 61 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/greg-s-corrado/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/greg-s-corrado/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Greg S. Corrado # Greg S. Corrado Greg S. Corrado works on machine learning at scale, and the papers here span two connected concerns. One is how neural models can learn useful numerical representations of words from very large text collections. The other is how the software systems that train such models can be built to run efficiently across many machines and kinds of hardware. Across both, the emphasis falls on simple models and designs that stay fast enough to handle billions of training examples. The most cited works on language address word vectors. [Efficient Estimation of Word Representations in Vector Space](https://md.research.elamur.ai/free/en/papers/mikolov-2013-efficient-estimation-word-representations-vector/) introduced two lightweight log-linear architectures without a nonlinear hidden layer. Continuous bag-of-words predicts a word from its averaged neighbours, while Skip-gram predicts the neighbours from the word. Training ran on a distributed framework so that very large corpora became practical. The follow-up, [Distributed Representations of Words and Phrases and their Compositionality](https://md.research.elamur.ai/free/en/papers/mikolov-2013-distributed-representations-words-phrases-their/), refined Skip-gram in several ways. It drops frequent words at random to speed training and help rare words. It adds negative sampling, a simplified alternative to noise-contrastive estimation. It also gives a statistical way to detect phrases and learn vectors for them. The newest paper here turns from models to infrastructure. [TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems](https://md.research.elamur.ai/free/en/papers/abadi-2016-tensorflow-large-scale-machine-learning/) describes the successor to Google's earlier distributed training system, which had become too inflexible for quick experimentation and difficult to deploy on small devices. The system expresses computations as stateful dataflow graphs of operations, with tensors flowing along the edges. These graphs can be executed on CPUs, GPUs and clusters, and this paper is the most cited of Corrado's papers here. Corrado is based at [Google (United States)](https://md.research.elamur.ai/free/en/companies/google/), and earlier bylines include [Stanford University](https://md.research.elamur.ai/free/en/universities/stanford-university/). Frequent co-authors on these papers include [Tomas Mikolov](https://md.research.elamur.ai/free/en/authors/tomas-mikolov/), [Kai Chen](https://md.research.elamur.ai/free/en/authors/kai-chen/) and [Jeff Dean](https://md.research.elamur.ai/free/en/authors/jeff-dean/), with whom the word-representation work was written. The systems work brought in a wider group, among them [Ilya Sutskever](https://md.research.elamur.ai/free/en/authors/ilya-sutskever/) and [Paul Barham](https://md.research.elamur.ai/free/en/authors/paul-barham/). Greg S. Corrado has 3 papers in our library, in 2013–2016; often with [Jeff Dean](https://md.research.elamur.ai/free/en/authors/jeff-dean/), [Kai Chen](https://md.research.elamur.ai/free/en/authors/kai-chen/), [Tomas Mikolov](https://md.research.elamur.ai/free/en/authors/tomas-mikolov/). 3 papers in our library · 2013–2016 [OpenAlex](https://openalex.org/A5068955381) · [ORCID](https://orcid.org/0000-0001-8817-0992) · [Wikidata](https://www.wikidata.org/wiki/Q24803072) · [**h-index 61**](https://openalex.org/authors/A5068955381) · [129 works](https://openalex.org/works?filter=author.id:A5068955381) · [93,877 citations](https://openalex.org/works?filter=author.id:A5068955381&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 3 works in our library](https://md.research.elamur.ai/free/en/authors/greg-s-corrado/#papers) · [🔗 9,133 citations in our library](https://md.research.elamur.ai/free/en/authors/greg-s-corrado/cited-by/) · [1 more in our library without a page yet](#also) · [⭐ Paper Star rank #90](https://md.research.elamur.ai/free/en/paper-stars/#star-90) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Greg+S.+Corrado) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Greg+S.+Corrado) · [dblp](https://dblp.org/search?q=Greg+S.+Corrado) · [ACL Anthology](https://aclanthology.org/search/?q=Greg+S.+Corrado) ## Affiliations [🏢**Google** Mountain View · United States 2012–2026 · 110 papersEmployment*current*](https://md.research.elamur.ai/free/en/companies/google/) · [🎓**Stanford University** Stanford · United States 2004–2019 · 9 papers](https://md.research.elamur.ai/free/en/universities/stanford-university/) · [🔬**Howard Hughes Medical Institute** Chevy Chase · United States 2004–2019 · 6 papers](https://ror.org/006w34k90) · [🏥**Stanford Medicine** Stanford · United States 2004–2019 · 6 papers](https://md.research.elamur.ai/free/en/hospitals/stanford-medicine/) · [🎓**Princeton University** Princeton · United States 2000–2003 · 3 papers](https://md.research.elamur.ai/free/en/universities/princeton-university/) · [🔬**Max Planck Institute for Biological Cybernetics** Tübingen · Germany 2007 · 2 papers](https://ror.org/026nmvv73) · [🔬**Max Planck Society** Munich · Germany 2007 · 2 papers](https://md.research.elamur.ai/free/en/labs/max-planck-society/) · [🎓**Massachusetts Institute of Technology** Cambridge · United States 2001–2005 · 2 papers](https://md.research.elamur.ai/free/en/universities/massachusetts-institute-of-technology/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed. ## Works by year ### 2010s [**2016** 1 paper](https://md.research.elamur.ai/free/en/papers/abadi-2016-tensorflow-large-scale-machine-learning/) · [**2013** 2 papers](https://md.research.elamur.ai/free/en/authors/greg-s-corrado/year/2013/) ## Papers The most cited first (OpenAlex and our library). 1. **[TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems](https://md.research.elamur.ai/free/en/papers/abadi-2016-tensorflow-large-scale-machine-learning/)** *(2016 · 9,453 citations)* Google's first-generation distributed training system, DistBelief, was used by more than 50 teams. It proved too rigid for fast research and hard to bring to small devices. This white paper presents TensorFlow, its successor. TensorFlow is both an interface for defining machine learning computations and a system for… 2. **[Distributed Representations of Words and Phrases and their Compositionality](https://md.research.elamur.ai/free/en/papers/mikolov-2013-distributed-representations-words-phrases-their/)** *(2013 · 4,233 citations)* The paper extends the Skip-gram model, which learns vector representations of words by predicting neighboring words in a text. 3. **[Efficient Estimation of Word Representations in Vector Space](https://md.research.elamur.ai/free/en/papers/mikolov-2013-efficient-estimation-word-representations-vector/)** *(2013 · 3,846 citations)* Most NLP systems of that time treated words as separate indices in a vocabulary, so similarity between words was not taken into account at all. ## Also in our library 1 more work of theirs is in our library without a page here yet; it will appear as we publish them. ## Co-authors here 8 co-authors with a page, the most papers together first. - [Jeff Dean](https://md.research.elamur.ai/free/en/authors/jeff-dean/) ×3 - [Kai Chen](https://md.research.elamur.ai/free/en/authors/kai-chen/) ×2 - [Tomas Mikolov](https://md.research.elamur.ai/free/en/authors/tomas-mikolov/) ×2 - [Eugene Brevdo](https://md.research.elamur.ai/free/en/authors/eugene-brevdo/) - [Ian Goodfellow](https://md.research.elamur.ai/free/en/authors/ian-goodfellow/) - [Ilya Sutskever](https://md.research.elamur.ai/free/en/authors/ilya-sutskever/) - [Paul Barham](https://md.research.elamur.ai/free/en/authors/paul-barham/) - [Zhifeng Chen](https://md.research.elamur.ai/free/en/authors/zhifeng-chen/) ## Cited by Papers of our library cite their works 9,133 times (of the 140,884 papers whose bibliographies we read); [618 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/greg-s-corrado/cited-by/).