CV

A full CV is available on request.

Education

PhD Automatic Control: 2013 - 2018 (expected), Linköping University, Department of Electrical Engineering.; Research topic is mathematical aspects of machine learning, signal processing and system identification.
MSE in Applied physics and electrical engineering - international, Chinese: 2007 - 2013, Linköping University.; Specialization in control- and information systems. Courses in advanced signal processing, mathematics and automatic control.
BSc in Mathematics: 2007 - 2012, Linköping University.; BSc with a focus in applied mathematics and machine learning.

Work experience

Teaching assistant: 2013 - Current, Linköping University, Department of Electrical Engineering.; Teach courses in automatic control, mathematical modeling, simulation and signal processing.
Thesis worker: 2013, Autoliv Electronics.; Prototyped and developed a camera and radar sensor fusion system for vehicle tracking.
Teaching assistant: 2012, Linköping University, Department of Electrical Engineering.; Taught courses in basic automatic control.
Tutor: Aug - Oct 2011, Linköping University, Department of Mathematics.; Tutor in the fundamental mathematics course given to all first year engineering students.

Awards and grants

Best Paper Award - International Conference on Artificial Intelligence and Statistics, Fort Lauderdale, USA, April 2017.
Fulbright Grant - Fulbright Visiting Student Researcher with Prof. David M. Blei, Columbia University in the City of New York, USA, August 2016 - June 2017.
Best Poster Award - Summer School on Deep Learning for Image Analysis, Denmark, August 2014.

Language proficiency

Swedish - native proficiency

English - full professional proficiency

Chinese - working proficiency

Select publications

C. A. Naesseth, F. J. R. Ruiz, S. Linderman, D. M. Blei, Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms, Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS), Fort Lauderdale, USA, April 2017.

C. A. Naesseth, F. Lindsten and T. B. Schön, Nested Sequential Monte Carlo Methods, Proceedings of the 32nd International Conference on Machine Learning (ICML), Lille, France, July 2015.

C. A. Naesseth, F. Lindsten and T. B. Schön, Sequential Monte Carlo for Graphical Models, Advances in Neural Information Processing Systems (NIPS) 27, Montreal, Canada, December 2014.