The main goal of my research is to develop scalable statistical modeling and inference methods for nonlinear dynamic systems and to apply these methods in applications such as biomedical engineering, target tracking, and sensor networks. The research is in the intersection of statistical signal processing, probabilistic machine learning, and sensor systems as it combines Bayesian filtering, smoothing, and parameter estimation methods with probabilistic modeling and leverages the advances of sensor technology.
I received the Dipl. Ing. degree in Electrical and Communication Engineering from Bern University of Applied Sciences, Switzerland in 2007, the M.Sc. in Electrical Engineering and Ph.D. in Automatic Control all from Luleå University of Technology, Sweden in 2009 and 2014, respectively. I have held visiting positions at the Department of Electrical and Computer Engineering at Stony Brook University, NY, USA (2013, host: Prof. Petar Djurić) and the Department of Engineering at the University of Cambridge, UK (2017, host: Prof. Simon J. Godsill). Between 2014 and 2016, I was a Post-Doctoral Researcher at Luleå University of Technology and between 2016 and 2019, I was a Post-Doctoral Researcher (2016 — 2017) and Research Fellow (2018 — 2019) at the Department of Electrical Engineering and Automation at Aalto University, Finland.