Panos Ipeirotis
Merchant S Council Professor Of Business And Technology at NYU Stern School of Business
New York, New York, United States
Summary
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Rockstar🎓
Top SchoolPanos Ipeirotis is the Merchant’s Council Professor of Business and Technology at NYU Stern and a veteran researcher bridging computer science, data science, and economics with over two decades of academic and industry impact. He pioneered work on social media, user-generated content and crowdsourcing—recognized by the 2015 Lagrange Prize and a 2020 KDD Test-of-Time award—and holds a PhD in Computer Science from Columbia. Beyond academia he has founded and exited a startup, led AI product efforts at Compass that drove meaningful revenue, and consulted for organizations like Citi and the World Bank, translating research into production systems. An active open-source contributor, he has improved the scholarly Python package to make Google Scholar data retrieval more robust against CAPTCHAs, reflecting his hands-on approach to practical tooling. Based in New York, he combines deep theoretical pedigree with repeated entrepreneurial and product successes that shape both research and real-world AI deployment.
14 years of coding experience
24 years of employment as a software developer
Diploma Computer Engineering and Informatics, Diploma Computer Engineering and Informatics at University of PatrasPhD Computer Science, PhD Computer Science at Columbia University
Greek, English
Stackoverflow
21reputation
0reached
1answer
0questions
Github Skills (9)
beautifulsoup10
python10
webscraping10
http-request10
testing9
javascript6
privacy6
data-protection6
mousemove6
Programming languages (6)
Github contributions (5)
scholarly-python-package/scholarly
May 2020 - May 2022
Retrieve author and publication information from Google Scholar in a friendly, Pythonic way without having to worry about CAPTCHAs!
Role in this project:
Back-end Developer
Back-end DeveloperContributions:12 releases, 24 reviews, 199 commits in 2 years
Contributions summary:Panos primarily worked on enhancing the `scholarly` Python package, which interacts with Google Scholar. Their contributions focused on improving the package's robustness and functionality, as evidenced by changes to the core `scholarly.py` and `test.py` files. They implemented features related to proxy usage and error handling, specifically dealing with CAPTCHAs and other problematic responses from Google Scholar. These changes improved the package's reliability when retrieving information from Google Scholar.
citation-analysispythonscholarly-articlesgooglescholarcitation-network
ipeirotis/ReadabilityMetrics
Mar 2012 - Sep 2022
Contributions:20 commits, 1 PR, 6 pushes in 10 years 7 months
followingindexflesch-kincaid-grade-levelfoggrade
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