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Simo Särkkä
Department of Electrical Engineering and Automation

Simo Särkkä

Professor (Associate Professor)

Contact information

Postal address
Otakaari 3 / Rakentajanaukio 2 c
Mobile phone
+358505124393
Full researcher profile
https://research.aalto.fi/...

Description

Dr. Särkkä is an Associate Professor in Sensor informatics and medical technology at the Department of Electrical Engineering and Automation (EEA) at Aalto University. His research interests are in multi-sensor data processing systems with applications in location sensing, health and medical technology, machine learning, inverse problems, and brain imaging.

Honors and awards

Award or honor granted for academic career
Department of Electrical Engineering and Automation
Jan 2014

Winner of the 1st Prize for Reproducibility in Signal Processing by soundsoftware.ac.uk, awarded at Machine Learning for Signal Processing (MLSP) Conference 2014 Winner of the 1st Prize for Reproducibility in Signal Processing by soundsoftware.ac.uk, awarded at Machine Learning for Signal Processing (MLSP) Conference 2014.

Award or honor granted for a specific work
Department of Electrical Engineering and Automation
Jan 2004

Winner of the IJCNN Time Series Prediction Competition - The CATS Benchmark (together with Vehtari & Lampinen) Winner of the IJCNN Time Series Prediction Competition - The CATS Benchmark (together with Vehtari & Lampinen), 2004 (24 international contestants).

Award or honor granted for a specific work
Professorship Rousu J.
Dec 2017

Best paper finalist and runner-up award, Computer Track The first IEEE Life Sciences Conference (LSC), best paper finalist and runner up award for the Computer track for the paper "Prediction of major complications affecting very low birth weight infants" by Olli-Pekka Rinta-Koski, Simo Särkkä, Jaakko Hollmén, Markus Leskinen, Krista Rantakari and Sture Andersson

Award or honor granted for a specific work
Department of Electrical Engineering and Automation
Jan 2016

The best student paper award winner The best student paper award winner for paper "Jakub Prüher and Simo Särkkä (2016). On The Use Of Gradient Information In Gaussian Process Quadratures. In Proceedings of IEEE International Workshop on Machine Learning for Signal Processing (MLSP)."

Award or honor granted for a specific work
School common, ELEC
Jul 2016

Tammy L. Blair Best Student Paper Award, First Runner-Up

Award or honor granted for a specific work
Department of Electrical Engineering and Automation
Jul 2017

Tammy L. Blair Best Student Paper Award, First Runner-Up

Research groups

Helsinki Institute for Information Technology HIIT

Publications

Department of Electrical Engineering and Automation

Numerical integration as a finite matrix approximation to multiplication operator

Publishing year: 2019 Journal of Computational and Applied Mathematics
Department of Electrical Engineering and Automation

Iterative statistical linear regression for Gaussian smoothing in continuous-time non-linear stochastic dynamic systems

Publishing year: 2019 Signal Processing
Department of Electrical Engineering and Automation

Student's t-Filters for Noise Scale Estimation

Publishing year: 2019 IEEE Signal Processing Letters
Department of Electrical Engineering and Automation

Bounds on the Covariance Matrix of a Class of Kalman-Bucy Filters for Systems with Non-Linear Dynamics

Publishing year: 2019 Proceedings of 57th IEEE Conference on Decision and Control, CDC 2018
Helsinki Institute for Information Technology HIIT, Department of Electrical Engineering and Automation

A probabilistic model for the numerical solution of initial value problems

Publishing year: 2019 STATISTICS AND COMPUTING
Department of Electrical Engineering and Automation

Rao-Blackwellized Gaussian Smoothing

Publishing year: 2019 IEEE Transactions on Automatic Control
Department of Electrical Engineering and Automation

A Bayes–Sard Cubature Method

Publishing year: 2018 Advances in Neural Information Processing Systems 31
Department of Electrical Engineering and Automation

On-line Bayesian parameter estimation in electrocardiogram state space models

Publishing year: 2018 2018 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2018 - Proceedings
Department of Electrical Engineering and Automation

Mixture representation of the matérn class with applications in state space approximations and Bayesian quadrature

Publishing year: 2018 Proceedings of the 2018 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2018
Department of Electrical Engineering and Automation, Department of Neuroscience and Biomedical Engineering

Tracking of dynamic functional connectivity from MEG data with Kalman filtering

Publishing year: 2018 Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018