Lars Hammarstrand

Assistant professor, Electrical engineering

Lars Hammarstrand is an Assistant Professor in the Signal processing research group. His main research interests are in the intersection of machine learning and Bayesian inference, especially with application to mapping, self- localization, object tracking, sensor data fusion for self-driving vehicles. Lars is the coordinator for Chalmers efforts surrounding the development of a self-driving vehicle through the project COPPLAR: He also supervises PhD students and teaches graduate and undergraduate courses in, e.g., non-linear filtering and linear systems and transforms.
SSY345 Sensor fusion and non-linear filtering
ChalmersX Sensor fusion and nonlinear filtering for automotive systems on EdX
PGM Probabilsitic Graphical Models​
TMA982 Linear systems and transforms

Published: Mon 12 Aug 2019.