September 30, 2011, Webb 1100

Internet advertising revenues in the US hit $7.3 billion for the first quarter of 2011. This already large number together with the 23% year over year growth underscores the significance of online advertising as an industry and reflects the fact that the world is entering the media economy. Despite the current state of the economy, internet ad spending is expected to continue increasing faster than most other industry sectors. One way of turning this growing industry into a viable business is by providing algorithmic match making between advertisers and publishers in an ad network; i.e., by figuring out where, when, and how to show ads to the satisfaction of publishers and advertisers while maximizing the profit of the network. An ad network is a good example of a complex and very high-dimensional optimization problem and the presentation will describe interesting properties of this system. The presentation will also show how the problem leads to interesting but challenging feedback control problems, and how some of these can be solved.

Dr. Niklas Karlsson directs Algorithm Research within Advertising.com Group R&D, Aol, with a focus on optimal ad- and content distribution. His duties include leading a team of engineers and scientists to recognize business needs, formulate the needs as mathematical problems, and solve the problems for optimal yield, robustness, and scalability. Among his and his team’s accomplishments is the development of the AdLearn 5 campaign delivery system, which is a decentralized, automated, and feedback-based control system providing improved performance and capacity. Beyond AdLearn, Karlsson is also the lead scientist and visionary behind Aol’s next generation unified Ad and Content optimization system.

Karlsson joined Advertising.com/AOL in August 2005 from Evolution Robotics, where he was responsible to develop novel navigation and control algorithms for autonomous mobile robots. In that role, he invented among other things the vSLAM navigation system for which he has been awarded several US patents. Prior to joining Evolution Robotics in 2002, Karlsson was a researcher and Ph.D. student at University of California at Santa Barbara. His research spanned applied and theoretical research of feedback control algorithms for suspension and traction control of vehicles and stability control of buildings.

Karlsson holds 14 patents (with an additional 8 pending) in the area of algorithms for Internet advertising and navigation of autonomous robots, has published a range of scientific papers, and serves as reviewer for various journals and conferences. He holds an M.S. in Engineering Physics from University of Lund, Sweden; an M.A. in Statistics and Applied Probability and a Ph.D. in Control theory, Dynamic Systems, and Robotics from University of California at Santa Barbara.