Panagiotis Ipeirotis

About

Panos Ipeirotis is a professor with a focus on research related to data, crowdsourcing, and machine learning. His work encompasses a broad range of topics within these areas, contributing to the understanding and development of innovative solutions in data-driven fields. The page highlights his role as an academic and researcher, with a history of mentoring students and engaging in scholarly activities. His professional background includes supervising numerous PhD students and participating in research projects that advance knowledge in his areas of expertise.

Research topics

• Computer Science
• Machine Learning
• Artificial Intelligence
• Economics
• Psychology
• Political Science
• Engineering
• World Wide Web
• Knowledge management
• Social psychology

Selected publications

• The Dynamics of Micro-Task Crowdsourcing

  2015-05-18 · 189 citations

  article

  Micro-task crowdsourcing is rapidly gaining popularity among research communities and businesses as a means to leverage Human Computation in their daily operations. Unlike any other service, a crowdsourcing platform is in fact a marketplace subject to human factors that affect its performance, both in terms of speed and quality. Indeed, such factors shape the dynamics of the crowdsourcing market. For example, a known behavior of such markets is that increasing the reward of a set of tasks would…

  PublisherDOI

• Reputation Transferability in Online Labor Markets

  Management Science · 2015-07-09 · 162 citations

  articleSenior author

  Online workplaces such as oDesk, Amazon Mechanical Turk, and TaskRabbit have been growing in importance over the last few years. In such markets, employers post tasks on which remote contractors work and deliver the product of their work online. As in most online marketplaces, reputation mechanisms play a very important role in facilitating transactions, since they instill trust and are often predictive of the employer’s future satisfaction. However, labor markets are usually highly heterogeneou…

  PublisherDOI

• Modeling Consumer Footprints on Search Engines: An Interplay with Social Media

  Management Science · 2018-06-11 · 89 citations

  article

  It is now well understood that social media plays an increasingly important role in consumers’ decision making. However, an overload of social media content in product search engines can hinder consumers from efficiently seeking information. We propose a structural econometric model to understand consumers’ preferences and costs on search engines to improve user experience under unstructured social media. Our model combines an optimal stopping framework with an individual-level random utility ch…

  PublisherDOI

• Demand-Aware Career Path Recommendations: A Reinforcement Learning Approach

  Management Science · 2020 · 57 citations

  Senior authorCorresponding

  A skill’s value depends on dynamic market conditions. To remain marketable, contractors need to keep reskilling themselves continuously. But choosing new skills to learn is an inherently hard task: Contractors have very little information about current and future market conditions, which often results in poor learning choices. Recommendation frameworks could reduce uncertainty in learning choices. However, conventional approaches would likely be inefficient; they would model previous (often poor…

  PublisherDOI

• Getting More for Less

  2015-05-18 · 48 citations

  articleOpen access

  In crowdsourcing systems, the interests of contributing participants and system stakeholders are often not fully aligned. Participants seek to learn, be entertained, and perform easy tasks, which offer them instant gratification; system stakeholders want users to complete more difficult tasks, which bring higher value to the crowdsourced application. We directly address this problem by presenting techniques that optimize the crowdsourcing process by jointly maximizing the user longevity in the s…

  PublisherOA PDFDOI

Recent grants

• CAREER: Towards a Text-Centric Database Management System

  NSF · $500k · 2007–2012

Frequent coauthors

• Luis Gravano

  44 shared

• Anindya Ghose

  New York University

  33 shared

• Foster Provost

  15 shared

• Jing Wang

  15 shared

• Beibei Li

  14 shared

• Mehran Sahami

  11 shared

• Marios Kokkodis

  10 shared

• Victor S. Sheng

  Texas Tech University

  9 shared

Labs

• Panos Ipeirotis LabPI

Education

• Ph.D., Computer Science

  Columbia University

  2005

• M.S., Computer Science

  Columbia University

  2002

• B.S., Computer Science

  National Technical University of Athens

  1998

Awards & honors

• 2015 Lagrange Prize in Complex Systems
• 2020 Test of Time award at KDD
• More than ten “Best Paper” awards and nominations
• CAREER award from the National Science Foundation

Similar researchers at New York University

• Jiawei Zhangh-76
• Chao Lih-49