Michael Kaess is interested in mobile robot autonomy. One of the first problems encountered when robots operate outside controlled factory and research environments is the need to perceive their surroundings. His research focuses on efficient inference at the connection of linear algebra and probabilistic graphical models for 3D mapping and localization.
Kaess has previously been a research scientist and a postdoctoral associate at the Massachusetts Institute of Technology (MIT), in John Leonard’s Marine Robotics Lab. In 2008 he received his Ph.D. in Computer Science from the Georgia Institute of Technology, advised by Frank Dellaert.
2008 Ph.D., Computer Science, Georgia Institute of Technology
2002 MS, Computer Science, Georgia Institute of Technology
1998 BS, Computer Science (Vordiplom Informatik), University of Karlsruhe