Support The World's Smartest Network
×

Help the New York Academy of Sciences bring late-breaking scientific information about the COVID-19 pandemic to global audiences. Please make a tax-deductible gift today.

DONATE
This site uses cookies.
Learn more.

×

This website uses cookies. Some of the cookies we use are essential for parts of the website to operate while others offer you a better browsing experience. You give us your permission to use cookies, by continuing to use our website after you have received the cookie notification. To find out more about cookies on this website and how to change your cookie settings, see our Privacy policy and Terms of Use.

We encourage you to learn more about cookies on our site in our Privacy policy and Terms of Use.

NYCE 2012: New York Computer Science & Economics Day

NYCE 2012: New York Computer Science & Economics Day

Monday, December 3, 2012

Simons Foundation, NYC

 

NYCE 2012 is the fifth annual New York Computer Science & Economics (NYCE) day. The goal of the meeting is to bring together researchers in the larger New York metropolitan area with interests in computer science, economics, marketing, and business, and with a common focus on understanding and developing the economics of Internet activity. Topics of interest to the NYCE community include (but are not limited to) theoretical, modeling, algorithmic, and empirical work on advertising and marketing based on search, user-generated content, or social networks, and other means of monetizing the Internet.

This year, our organizing theme will be the economics of big data, information, and privacy. Buoyed by internet-scale services and the arrival of big data, in recent years information itself has become a valuable commodity. But as a commodity, it has certain properties that distinguish it from the goods of classical economic theory. It can be copied at no cost, not only by the seller, but by the buyers as well. Agents' costs for information may be rooted in privacy concerns, which requires new definitions, and may be a function not only of the outcome chosen by a mechanism, but of the process by which the mechanism chooses an outcome itself. And because of the scale of cloud-sized data, computational efficiency becomes a first-order design constraint. These topics have begun to be studied very recently, and this workshop will foster this study by bringing together researchers approaching this problem from different fields and different perspectives, with the goal of developing a better high level understanding of these issues, and to encourage new collaborations.

Organizers

Dirk Bergemann, PhD

Yale University

Sham Kakade, PhD

Microsoft Research

Nitish Korula, PhD

Google Research

Aaron Roth, PhD

University of Pennsylvania

Speakers

Alessandro Acquisiti

Carnegie Mellon University

Moshe Babaioff

Microsoft Research

Tim Roughgarden

Stanford University

Catherine Tucker

Massachusetts Institute of Technology

Visit the NYCE 2012 event page for more information.