The use of the internet has led to the creation of fundamentally new forms of advertising.  In turn, this advertising provides the financial support for many on-line companies and technological breakthroughs.

The development of online advertising has raised many new questions in economics, mathematics, computer science and engineering, particularly around the design of auctions and markets, and in the design of algorithms to efficiently manage them.  In this talk, we will survey a few problems in internet advertising and discuss some algorithmic and game-theoretic issues that arise.  We will discuss problems both in sponsored search and in display advertising.  We will describe  the applications, the algorithmic problems that arise, and the solutions obtained. In particular, we will discuss the problem of how an advertiser should allocate its budget among various keywords in a sponsored search auction, and how a publisher should decide which display ads to accept.

 Clifford Stein is Professor and Chair of the Industrial Engineering and Operations Research Department at Columbia University. He also holds an appointment as Professor of Computer Science at Columbia.  He received his B.S.E. from Princeton University in 1987 and his Ph.D. degree from MIT in 1992.  His research interests include the design and analysis of algorithms, combinatorial optimization, operations research, network algorithms, scheduling, algorithm engineering and internet algorithms.  He has published over 60 scientific papers and occupied a variety of editorial positions including the journals ACM Transactions on Algorithms, Mathematical Programming, Journal of Algorithms, SIAM Journal on Discrete Mathematics and Operations Research Letters. He has been the recipient of an NSF Career Award, an Alfred Sloan Research Fellowship and the Karen Wetterhahn Award for Distinguished Creative or Scholarly Achievement. He is also the co-author of the two textbook, Introduction to Algorithms, with T. Cormen, C. Leiserson and R. Rivest and Discrete Math for Computer Science, with Ken Bogart and Scot Drysdale.