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Michele Catasta

Michele Catasta has 2 papers in our library, in 2023, most of them on Code & programming languages; often with Joshua Howland, Kefan Xiao, Abhishek Rao.

2 papers in our library · 2023

OpenAlex · ORCID · h-index 20 · 62 works · 4,057 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 3,880 times in our library · 4 more in our library without a page yet · ⭐ Paper Stars ranking: #8753

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓École Polytechnique Fédérale de LausanneLausanne · Switzerland2010–2017 · 25 papers🎓Stanford UniversityStanford · United States2017–2023 · 12 papersEmployment🏢GoogleMountain View · United States2022–2023 · 3 papers🎓Ollscoil na Gaillimhe – University of GalwayGalway · Ireland2008–2009 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksInformation Systems · 2 worksLanguage and Linguistics · 2 worksComputer Science Applications · 1 work

🧭 Topics 1Research subjects and languages the work is about.Code & programming languages · 2 works

 Works by year

2020s

20232 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Natural Language to Code Generation in Interactive Data Science Notebooks (2023 · 63 citations)
    Data scientists often work in Jupyter-style notebooks, where each new request to an AI coding assistant depends on earlier cells, their execution state, and previous requests.
  2. Measuring The Impact Of Programming Language Distribution (2023 · 22 citations)
    Code LLMs are usually trained on GitHub data, where each language's share reflects how much code exists rather than how many developers use it.

All works

6 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. Open Graph Benchmark: Datasets for Machine Learning on Graphs ↗arXiv:2005.00687 · no summary yetWeihua Hu et al.2020 · 712 citations
  2. Language-Agnostic Representation Learning of Source Code from Structure and Context ↗arXiv:2103.11318 · no summary yetDaniel Zügner et al.2021 · 85 citations
  3. Natural Language to Code Generation in Interactive Data Science NotebooksAnnual Meeting of the Association for Computational Linguistics (ACL)Pengcheng Yin, Wen-Ding Li, Kefan Xiao, et al.2023 · 63 citations
  4. SAGE: A Hybrid Geopolitical Event Forecasting System ↗International Joint Conference on Artificial Intelligence · no summary yetFred Morstatter et al.2019 · 24 citations
  5. Measuring The Impact Of Programming Language DistributionarXiv:2302.01973Gabriel Orlanski, Kefan Xiao, Xavier Garcia, et al.2023 · 22 citations
  6. Hybrid forecasting of geopolitical events† ↗AI Magazine · no summary yetDaniel M. Benjamin et al.2023 · 18 citations

 Co-authors here

12 of 16 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 3,880 times (of the 149,439 papers whose bibliographies we read); 1,001 citing papers with a page here →.

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