Human Computation and Crowdsourcing


July 16, 2012


Eric Horvitz, Luis von Ahn, Rajesh Patel, and Yiling Chen


Computer Science Dept, Harvard, Microsoft Research, Bing Core Relevance group


Ece Kamar from Microsoft Research chairs this session at Faculty Summit 2012.

In recent years, human computation and crowdsourcing have emerged as an important research area in computer science. Crowdsourcing aims at using human intelligence for solving tasks that computers cannot easily do alone. The work in this area varies among different applications of crowdsourcing, investigations of best practices for crowdsourcing, and formal approaches for building more efficient and reliable crowdsourcing systems. There is a strong interest in crowdsourcing research among a wide audience working in different areas of computer science, which may benefit from having easy and programmatic access to human intelligence.

This session aims at bringing together leading researchers in the area of crowdsourcing to exchange information about recent developments and best practices, and to discuss opportunities for future research.


Eric Horvitz, Luis von Ahn, Rajesh Patel, and Yiling Chen

Luis von Ahn is a Postdoctoral Fellow in the Computer Science Department at Carnegie Mellon University, where he also received his Ph.D. in 2005. Previously, Luis obtained a B.S. in mathematics from Duke University in 2000. He is the recipient of a Microsoft Research Fellowship. His research interests include encouraging people to do work for free, as well as catching and thwarting cheaters in online environments. His work has appeared in over 100 news outlets including The New York Times, CNN, USA Today, The BBC, and The Discovery Channel. Luis holds 4 patent applications, and has licensed technology to major Internet companies.

Yiling Chen is an Assistant Professor of Computer Science at Harvard University. She received her Ph.D. in Information Sciences and Technology from the Pennsylvania State University. Prior to working at Harvard, she spent two years at the Microeconomic and Social Systems group of Yahoo! Research in New York City. Her general research interests are on the border of computer science and economics. She is interested in designing and analyzing social computing systems according to both computational and economic objectives.

Eric Horvitz, today’s guest, joined Microsoft Research with two colleagues in 1993 to form the Decision Theory and Adaptive Systems group. Since then he has been at the center of a variety of projects focused on machine intelligence and adaptation, and the related tasks of information discovery, collection, and delivery.

Rajesh Patel works in a Bing Core Relevance group, on the team responsible for human relevance platform, measurement and crowdsourcing. He has been at Microsoft for 11+ years and worked on various projects (Office SharePoint Server, MDM, System Center data warehouse and SQL Server group). Since 2008 he is driving the efforts to develop Microsoft’s first Human Annotation Platform which is flexible, scalable and easy to use for any kind of human annotation needs. He is currently working on to bring crowdsourcing solution on UHRS platform to enable Bing and partner teams across Microsoft for flexible human annotations and judge pool needs.