In addition to his academic career, Ipeirotis has held research and engineering roles at Meta Reality Labs, Google, and Compass, Inc., where he led the development of predictive analytics systems.[12] He is also the author of the blog "A Computer Scientist in a Business School," which covers topics in crowdsourcing, data science, and academia; posts from the blog have been cited in academic papers and media coverage.[11][13]
Ipeirotis began his academic career as a graduate research assistant at Columbia University (1999–2004). In 2004, he joined the Department of Information, Operations, and Management Sciences at the New York University Stern School of Business as an Assistant Professor. He was promoted to Associate Professor in 2010 and Full Professor in 2016.[1]
He holds a courtesy appointment at the Courant Institute of Mathematical Sciences and is a faculty member at the NYU Center for Data Science. In 2013, Bloomberg Businessweek profiled him as the "data dude" of business analytics for his work on internet crowdsourcing and data quality.[11][1]
Research
Ipeirotis's work explores the intersection of computer science and economics, an approach he and collaborators have termed "EconoMining." His research has been published in venues such as Management Science, Information Systems Research, and IEEE Transactions on Knowledge and Data Engineering.[3]
Crowdsourcing and human computation
Ipeirotis is known for his studies on Amazon Mechanical Turk (MTurk). His 2010 paper "Running Experiments on Amazon Mechanical Turk," co-authored with Gabriele Paolacci and Jesse Chandler, established methodological standards for using crowdsourcing platforms in behavioral research and has been cited over 6,600 times.[15]
His research on MTurk data quality gained significant media attention. Studies revealing that approximately 40% of MTurk responses contained spam or low-quality content were covered by Business Insider, MIT Technology Review, and The Washington Post. His 2010 demographic analysis of the MTurk workforce became a widely cited reference for understanding crowd work platforms.[16]
This work led to the development of quality management techniques for crowdsourcing, including the "Get Another Label" framework for improving data quality using multiple noisy labelers, which received the SIGKDD Test of Time Award in 2020.
Data quality and record linkage
Ipeirotis has conducted extensive research on duplicate record detection and data quality. His 2007 survey "Duplicate Record Detection: A Survey" in IEEE Transactions on Knowledge and Data Engineering, co-authored with Ahmed Elmagarmid and Vassilios Verykios, became a standard reference in the database community with over 2,800 citations.[17]
Online reputation and user-generated content
His collaborative work with Anindya Ghose on the economic value of textual content in product reviews quantified the pricing power derived from user-generated content.[18] A related 2011 study demonstrated that the quality of spelling and grammar in product reviews significantly affects perceived helpfulness and product sales.[19] This finding was featured in Forbes, Harvard Business Review, Slate, Freakonomics, and Reuters.[20][21][22][23][24]
Awards and honors
2020:ACM SIGKDD Test of Time Award, for the 2008 paper "Get Another Label? Improving Data Quality and Data Mining Using Multiple, Noisy Labelers"
Archak, Nikolay; Ghose, Anindya; Ipeirotis, Panagiotis G. (2011). "Deriving the pricing power of product features by mining consumer reviews". Management Science. 57 (8): 1485–1509. doi:10.1287/mnsc.1110.1370.
Elmagarmid, Ahmed K.; Ipeirotis, Panagiotis G.; Verykios, Vassilios S. (2007). "Duplicate record detection: A survey". IEEE Transactions on Knowledge and Data Engineering. 19 (1): 1–16. doi:10.1109/TKDE.2007.250581.
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