Leo Kärkkäinen

1.6k total citations
64 papers, 1.1k citations indexed

About

Leo Kärkkäinen is a scholar working on Nuclear and High Energy Physics, Biomedical Engineering and Condensed Matter Physics. According to data from OpenAlex, Leo Kärkkäinen has authored 64 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Nuclear and High Energy Physics, 19 papers in Biomedical Engineering and 13 papers in Condensed Matter Physics. Recurrent topics in Leo Kärkkäinen's work include Quantum Chromodynamics and Particle Interactions (26 papers), High-Energy Particle Collisions Research (24 papers) and Acoustic Wave Phenomena Research (14 papers). Leo Kärkkäinen is often cited by papers focused on Quantum Chromodynamics and Particle Interactions (26 papers), High-Energy Particle Collisions Research (24 papers) and Acoustic Wave Phenomena Research (14 papers). Leo Kärkkäinen collaborates with scholars based in Finland, United States and United Kingdom. Leo Kärkkäinen's co-authors include Kari Rummukainen, K. Kajantie, P. Lacock, B. Petersson, D. Toussaint, Tom Blum, Y. Hancock, Antti‐Pekka Jauho, M. J. Puska and Janne M. J. Huttunen and has published in prestigious journals such as Nature, Physical Review B and Nuclear Physics B.

In The Last Decade

Leo Kärkkäinen

61 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Leo Kärkkäinen Finland 21 542 260 175 154 149 64 1.1k
R. Martone Italy 14 279 0.5× 68 0.3× 287 1.6× 85 0.6× 61 0.4× 128 824
Chiou-Ting Hsu Taiwan 26 737 1.4× 65 0.3× 202 1.2× 188 1.2× 117 0.8× 101 2.8k
Daniel Arndt United States 18 300 0.6× 22 0.1× 129 0.7× 92 0.6× 57 0.4× 33 1.5k
R. Jha India 16 573 1.1× 53 0.2× 69 0.4× 164 1.1× 79 0.5× 51 824
Ping Zhu China 20 549 1.0× 42 0.2× 148 0.8× 275 1.8× 90 0.6× 117 1.1k
T. Craciunescu Romania 13 292 0.5× 19 0.1× 94 0.5× 124 0.8× 84 0.6× 96 671
I. Pázsit Sweden 24 188 0.3× 44 0.2× 139 0.8× 356 2.3× 180 1.2× 227 2.1k
Andrew Pressley United Kingdom 18 233 0.4× 34 0.1× 62 0.4× 28 0.2× 133 0.9× 31 2.4k
J. Christiansen Canada 8 292 0.5× 25 0.1× 105 0.6× 37 0.2× 93 0.6× 10 1.3k
Marilyn K. Gordon United States 8 73 0.1× 25 0.1× 107 0.6× 67 0.4× 204 1.4× 11 1.4k

Countries citing papers authored by Leo Kärkkäinen

Since Specialization
Citations

This map shows the geographic impact of Leo Kärkkäinen'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 Leo Kärkkäinen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leo Kärkkäinen more than expected).

Fields of papers citing papers by Leo Kärkkäinen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Leo Kärkkäinen. 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 Leo Kärkkäinen. The network helps show where Leo Kärkkäinen may publish in the future.

Co-authorship network of co-authors of Leo Kärkkäinen

This figure shows the co-authorship network connecting the top 25 collaborators of Leo Kärkkäinen. A scholar is included among the top collaborators of Leo Kärkkäinen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Leo Kärkkäinen. Leo Kärkkäinen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kärkkäinen, Leo, et al.. (2022). On the scattering of a disk source by a rigid sphere for directivity broadening. The Journal of the Acoustical Society of America. 151(6). 4114–4125. 1 indexed citations
2.
Jaskari, Joel, Jaakko Sahlsten, Theodoros Damoulas, et al.. (2022). Uncertainty-Aware Deep Learning Methods for Robust Diabetic Retinopathy Classification. IEEE Access. 10. 76669–76681. 30 indexed citations
3.
Huttunen, Janne M. J., Leo Kärkkäinen, & Harri Lindholm. (2019). Pulse transit time estimation of aortic pulse wave velocity and blood pressure using machine learning and simulated training data. PLoS Computational Biology. 15(8). e1007259–e1007259. 37 indexed citations
4.
Huttunen, Janne M. J., Leo Kärkkäinen, Mikko Honkala, & Harri Lindholm. (2019). Deep learning for prediction of cardiac indices from photoplethysmographic waveform: A virtual database approach. International Journal for Numerical Methods in Biomedical Engineering. 36(3). e3303–e3303. 11 indexed citations
5.
Berglund, Mathias, et al.. (2015). Bidirectional recurrent neural networks as generative models. Neural Information Processing Systems. 28. 856–864. 65 indexed citations
6.
Kärkkäinen, Leo, et al.. (2013). Practical Procedure for Large Scale Personalized Head Related Transfer Function Acquisition. 1 indexed citations
7.
Kärkkäinen, Leo, et al.. (2008). Perceptual Evaluation of Numerically Simulated Head-Related Transfer Functions. Journal of the Audio Engineering Society. 4 indexed citations
8.
Huttunen, Tomi, et al.. (2007). Some Effects of the Torso on Head-Related Transfer Functions. Journal of the Audio Engineering Society. 4 indexed citations
9.
Huttunen, Tomi, et al.. (2007). SIMULATION OF THE TRANSFER FUNCTION FOR A HEAD-AND-TORSO MODEL OVER THE ENTIRE AUDIBLE FREQUENCY RANGE. Journal of Computational Acoustics. 15(4). 429–448. 14 indexed citations
10.
Kärkkäinen, Leo, et al.. (2006). On the sound field of a circular membrane in free space and an infinite baffle. The Journal of the Acoustical Society of America. 120(5). 2460–2477. 20 indexed citations
11.
Kärkkäinen, Leo, et al.. (2005). On the Sound Field of a Membrane in an Infinite Baffle. Journal of the Audio Engineering Society. 2 indexed citations
12.
Malinen, Mika, et al.. (2004). A FINITE ELEMENT METHOD FOR THE MODELING OF THERMO-VISCOUS EFFECTS IN ACOUSTICS. 22 indexed citations
13.
Kärkkäinen, Leo, et al.. (2004). A SOUND IN A BOX WITH DIFFERENT COMPLEX IMPEDANCES ON ITS WALLS. 1 indexed citations
14.
Blum, Tom, et al.. (1995). SU(3) lattice gauge theory with adjoint action at nonzero temperature. Nuclear Physics B - Proceedings Supplements. 42(1-3). 457–459. 2 indexed citations
15.
Blum, Tom, Steven Gottlieb, Leo Kärkkäinen, & D. Toussaint. (1995). The β function and equation of state of two flavor QCD. Nuclear Physics B - Proceedings Supplements. 42(1-3). 460–465. 4 indexed citations
16.
Bérnard, C., Thomas DeGrand, Anna Hasenfratz, et al.. (1994). Nature of the thermal phase transition with Wilson quarks. Physical review. D. Particles, fields, gravitation, and cosmology/Physical review. D. Particles and fields. 49(7). 3574–3588. 18 indexed citations
17.
Kärkkäinen, Leo, R. Lacaze, P. Lacock, & B. Petersson. (1994). Critical behaviour of the three-dimensional Gross-Neveu and Higgs-Yukawa models. Nuclear Physics B. 415(3). 781–796. 70 indexed citations
18.
Burda, Z., J. Jurkiewicz, & Leo Kärkkäinen. (1992). Universality of dynamically triangulated random surfaces in one-dimensional target space. Physics Letters B. 279(1-2). 41–46. 1 indexed citations
19.
Enqvist, Kari, K. Kajantie, Leo Kärkkäinen, & Kari Rummukainen. (1990). Constant field modes in lattice SU(3) gauge theory at large T. Physics Letters B. 249(1). 107–113. 6 indexed citations
20.
Kärkkäinen, Leo. (1990). Interface tension at Tc in hot Gluon matter. Nuclear Physics B - Proceedings Supplements. 17. 185–188. 1 indexed citations

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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