Dr. Niklas Karlsson is the Chief Scientist and VP of Research for Verizon Media's Programmatic Advertising Demand Side Platform (DSP). He is a visionary research leader with >17 years of industry experience in building R&D teams and developing algorithms for online advertising and for mobile robotics. His work on feedback control and AI has resulted in many successful products and 29 issued patents. From 2002 to 2005 he was the principal investigator of navigation and feedback control at Evolution Robotics, where he invented the break-through vSLAM technology (now used as the brain of a well-known market leading autonomous vacuum cleaner). In 2005 Karlsson joined Advertising.com/AOL, (later acquired by Verizon Communications) to build the research group responsible to develop the next generation advertising campaign control system. Under his hands-on leadership, the team has invented many components for optimization, control, and estimation that are now key components in the AdLearn optimization engine serving billions of ad impressions every day and delivering advertising budgets totaling 2 Billion US$ each year. As the Chief Scientist, he now defines the vision and directs the work on extremely big data sets and remarkably complicated dynamical systems.
Dr. Karlsson received a Ph.D. at UC Santa Barbara in Engineering with a focus on Control theory, Dynamic Systems, and Robotics; an M.A. in Statistics and Applied Probability from UCSB; an M.S. in Engineering Physics from Lund University; and is a graduate from Stanford Executive Program. Niklas received the Distinguished Alumni Award from the Department of Mechanical Engineering at UCSB in 2015 in recognition of "outstanding application of systems engineering principles to the field of online advertising," and the Master Inventor award from Oath Inc. in 2017 (the highest technology/science recognition within the company). He is frequently an invited speaker at national and international conferences in academia and industry.
Advertising Science, Data Science, Machine Learning, Optimization & Feedback Control, Scalable Systems