Simo Särkkä

8.6k citations

162 papers · 5.4k indexed · 4 hit papers · h-index 31

Impact in

Artificial Intelligence top 0.2%
- Target Tracking and Data Fusion in Sensor Networks
- Gaussian Processes and Bayesian Inference
Control and Systems Engineering top 0.5%
- Fault Detection and Control Systems
- Control Systems and Identification

Papers in ⓘ

Artificial Intelligence 109
- Target Tracking and Data Fusion in Sensor Networks 82
- Gaussian Processes and Bayesian Inference 46
Control and Systems Engineering 40
- Fault Detection and Control Systems 24
- Control Systems and Identification 21

Co-authors: Aapo Nummenmaa (3 shared papers)Jouni Hartikainen (10 shared papers)Arno Solin (14 shared papers)Aki Vehtari (9 shared papers)Lennart Svensson (6 shared papers)Jouko Lampinen (5 shared papers)Ángel F. García‐Fernández (12 shared papers)Robert Piché (4 shared papers)
Journals: IEEE Transactions on Automatic Control (12 papers)IEEE Transactions on Signal Processing (7 papers)Signal Processing (6 papers)IEEE Access (3 papers)Statistics and Computing (3 papers)
Partner nations: Finland United Kingdom Sweden

In The Last Decade

Simo Särkkä

151 papers receiving 5.2k citations

Hit Papers

align trajectories log scale

Bayesian Filtering and Smoothing 2023 · 101 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2023 Cambridge University Press eBooks
2013 Cambridge University Press eBooks
2009 IEEE Transactions on Automatic Control
2007 IEEE Transactions on Automatic Control

Peers

Countries citing papers authored by Simo Särkkä

Since Specialization

Citations

This map shows the geographic impact of Simo Särkkä's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Simo Särkkä with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Simo Särkkä more than expected).

Fields of papers citing papers by Simo Särkkä

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Simo Särkkä. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Simo Särkkä. The network helps show where Simo Särkkä may publish in the future.

Co-authors

The 25 scholars most cited alongside Simo Särkkä, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Simo Särkkä Line = papers co-authored together Simo Särkkä links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 162 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Bayesian Filtering and Smoothing Cambridge University Press eBooks ·Simo Särkkä Hit paper breakdown →	2013	1215
2	Recursive Noise Adaptive Kalman Filtering by Variational Bayesian Approximations IEEE Transactions on Automatic Control ·Simo Särkkä, Aapo Nummenmaa Hit paper breakdown →	2009	535
3	On Unscented Kalman Filtering for State Estimation of Continuous-Time Nonlinear Systems IEEE Transactions on Automatic Control ·Simo Särkkä Hit paper breakdown →	2007	406
4	Unscented Rauch--Tung--Striebel Smoother IEEE Transactions on Automatic Control ·Simo Särkkä	2008	230
5	Rao-Blackwellized particle filter for multiple target tracking Information Fusion ·Simo Särkkä, Aki Vehtari, Jouko Lampinen	2005	214
6	Sensors and AI Techniques for Situational Awareness in Autonomous Ships: A Review IEEE Transactions on Intelligent Transportation Systems ·Sarang Thombre, Zheng Zhao, Henrik Ramm-Schmidt, José M. Vallet García, Tuomo Malkamäki, Sergey Nikolskiy, Toni Hammarberg, Hiski Nuortie, M. Zahidul H. Bhuiyan, Simo Särkkä, Ville Lehtola	2020	177
7	Recursive outlier-robust filtering and smoothing for nonlinear systems using the multivariate student-t distribution Robert Piché, Simo Särkkä, Jouni Hartikainen	2012	151
8	Spatiotemporal Learning via Infinite-Dimensional Bayesian Filtering and Smoothing: A Look at Gaussian Process Regression Through Kalman Filtering IEEE Signal Processing Magazine ·Simo Särkkä, Arno Solin, Jouni Hartikainen	2013	149
9	Kalman filtering and smoothing solutions to temporal Gaussian process regression models Jouni Hartikainen, Simo Särkkä	2010	140
10	Dynamic retrospective filtering of physiological noise in BOLD fMRI: DRIFTER NeuroImage ·Simo Särkkä, Arno Solin, Aapo Nummenmaa, Aki Vehtari, Toni Auranen, Simo Vanni, Fa‐Hsuan Lin	2012	105
11	Bayesian Filtering and Smoothing Cambridge University Press eBooks ·Simo Särkkä, Lennart Svensson Hit paper breakdown →	2023	101
12	Posterior Linearization Filter: Principles and Implementation Using Sigma Points IEEE Transactions on Signal Processing ·Ángel F. García‐Fernández, Lennart Svensson, Mark R. Morelande, Simo Särkkä	2015	97
13	Non-linear noise adaptive Kalman filtering via variational Bayes Simo Särkkä, Jouni Hartikainen	2013	92
14	On Gaussian Optimal Smoothing of Non-Linear State Space Models IEEE Transactions on Automatic Control ·Simo Särkkä, Jouni Hartikainen	2010	83
15	Phase-Based UHF RFID Tracking With Nonlinear Kalman Filtering and Smoothing IEEE Sensors Journal ·Simo Särkkä, Ville Viikari, Miika Huusko, Kaarle Jaakkola	2011	82
16	Gaussian filtering and smoothing for continuous-discrete dynamic systems Signal Processing ·Simo Särkkä, Juha Sarmavuori	2012	77
17	Batch Continuous-Time Trajectory Estimation as Exactly Sparse Gaussian Process Regression Tim Barfoot, Chi Hay Tong, Simo Särkkä	2014	73
18	Rao-Blackwellized Monte Carlo Data Association for Multiple Target Tracking Simo Särkkä, Aki Vehtari, Jouko Lampinen	2004	61
19	Batch nonlinear continuous-time trajectory estimation as exactly sparse Gaussian process regression Autonomous Robots ·Sean Anderson, Timothy D. Barfoot, Chi Hay Tong, Simo Särkkä	2015	58
20	Cooperative Localization Using Posterior Linearization Belief Propagation IEEE Transactions on Vehicular Technology ·Ángel F. García‐Fernández, Lennart Svensson, Simo Särkkä	2017	45

About Simo Särkkä

Simo Särkkä is a scholar working on Artificial Intelligence, Control and Systems Engineering, Statistical and Nonlinear Physics, Statistics and Probability and Aerospace Engineering, having authored 162 papers that have together received 5.4k indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (82 papers), Gaussian Processes and Bayesian Inference (46 papers), Fault Detection and Control Systems (24 papers), Control Systems and Identification (21 papers), Inertial Sensor and Navigation (15 papers), Distributed Sensor Networks and Detection Algorithms (14 papers), Indoor and Outdoor Localization Technologies (12 papers) and Scientific Research and Discoveries (9 papers). The work is most often cited by research in Artificial Intelligence (3.1k citations), Control and Systems Engineering (1.4k citations), Aerospace Engineering (1.3k citations), Ocean Engineering (529 citations) and Signal Processing (353 citations). Simo Särkkä has collaborated with scholars based in Finland, United Kingdom and Sweden. Frequent co-authors include Aapo Nummenmaa, Jouni Hartikainen, Arno Solin, Aki Vehtari, Lennart Svensson, Jouko Lampinen, Ángel F. García‐Fernández, Robert Piché, Chi Hay Tong and Roland Hostettler. Their work appears in journals such as IEEE Transactions on Automatic Control, IEEE Transactions on Signal Processing, Signal Processing, IEEE Access and Statistics and Computing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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