Konrad Kowalczyk

1.3k total citations
74 papers, 978 citations indexed

About

Konrad Kowalczyk is a scholar working on Signal Processing, Computational Mechanics and Biomedical Engineering. According to data from OpenAlex, Konrad Kowalczyk has authored 74 papers receiving a total of 978 indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Signal Processing, 28 papers in Computational Mechanics and 17 papers in Biomedical Engineering. Recurrent topics in Konrad Kowalczyk's work include Speech and Audio Processing (54 papers), Advanced Adaptive Filtering Techniques (28 papers) and Music and Audio Processing (16 papers). Konrad Kowalczyk is often cited by papers focused on Speech and Audio Processing (54 papers), Advanced Adaptive Filtering Techniques (28 papers) and Music and Audio Processing (16 papers). Konrad Kowalczyk collaborates with scholars based in Poland, Germany and United Kingdom. Konrad Kowalczyk's co-authors include Maarten van Walstijn, Walter Kellermann, Edwin Mabande, Haohai Sun, Christian Bøhn, Emanuël A. P. Habets, Piotr Żelasko, Jakub Gałka, Archontis Politis and Daniel Krause and has published in prestigious journals such as The Journal of the Acoustical Society of America, Sensors and IEEE Signal Processing Magazine.

In The Last Decade

Konrad Kowalczyk

70 papers receiving 917 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Konrad Kowalczyk Poland 17 633 321 253 248 184 74 978
Martin Bouchard Canada 17 743 1.2× 288 0.9× 710 2.8× 134 0.5× 120 0.7× 102 1.2k
Futoshi Asano Japan 17 914 1.4× 148 0.5× 340 1.3× 368 1.5× 178 1.0× 70 1.2k
Rudolf Rabenstein Germany 18 820 1.3× 315 1.0× 461 1.8× 282 1.1× 270 1.5× 141 1.2k
Prasanga N. Samarasinghe Australia 19 987 1.6× 552 1.7× 540 2.1× 447 1.8× 129 0.7× 107 1.3k
Gerald Enzner Germany 19 909 1.4× 173 0.5× 834 3.3× 215 0.9× 117 0.6× 97 1.1k
Junfeng Li China 14 401 0.6× 122 0.4× 266 1.1× 174 0.7× 75 0.4× 139 797
Jesper Kjær Nielsen Denmark 15 426 0.7× 152 0.5× 265 1.0× 134 0.5× 61 0.3× 58 631
Takanobu Nishiura Japan 13 666 1.1× 130 0.4× 251 1.0× 103 0.4× 112 0.6× 157 830
Andy W. H. Khong Singapore 19 821 1.3× 107 0.3× 567 2.2× 65 0.3× 214 1.2× 143 1.2k
F. Asano Japan 14 425 0.7× 120 0.4× 231 0.9× 69 0.3× 67 0.4× 23 652

Countries citing papers authored by Konrad Kowalczyk

Since Specialization
Citations

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

Fields of papers citing papers by Konrad Kowalczyk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Konrad Kowalczyk

This figure shows the co-authorship network connecting the top 25 collaborators of Konrad Kowalczyk. A scholar is included among the top collaborators of Konrad Kowalczyk 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 Konrad Kowalczyk. Konrad Kowalczyk 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.
Villalba, Jesús, et al.. (2024). End-to-End Neural Speaker Diarization With Non-Autoregressive Attractors. IEEE/ACM Transactions on Audio Speech and Language Processing. 32. 3960–3973. 2 indexed citations
4.
Kowalczyk, Konrad, et al.. (2022). Spoken Language Recognition with Cluster-Based Modeling. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 6867–6871. 1 indexed citations
5.
Kowalczyk, Konrad, et al.. (2021). Sparse Linear Prediction-based Dereverberation for Signal Enhancement in Distant Speaker Verification. 2021 29th European Signal Processing Conference (EUSIPCO). 461–465. 1 indexed citations
6.
Kowalczyk, Konrad, et al.. (2018). Passive Joint Localization and Synchronization of Distributed Microphone Arrays. IEEE Signal Processing Letters. 26(2). 292–296. 29 indexed citations
7.
Żelasko, Piotr, et al.. (2017). Audio Replay Attack Detection Using High-Frequency Features. 27–31. 104 indexed citations
8.
Braun, Sebastian, Konrad Kowalczyk, & Emanuël A. P. Habets. (2015). Residual noise control using a parametric multichannel Wiener filter. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 360–364. 8 indexed citations
9.
Kowalczyk, Konrad, Oliver Thiergart, Maja Taseska, et al.. (2015). Parametric Spatial Sound Processing: A flexible and efficient solution to sound scene acquisition, modification, and reproduction. IEEE Signal Processing Magazine. 32(2). 31–42. 33 indexed citations
10.
Walstijn, Maarten van, et al.. (2014). A Spherical Array Approach for Simulation of Binaural Impulse Responses using the Finite Difference Time Domain Method. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 5 indexed citations
11.
Chakrabarty, Soumitro, Konrad Kowalczyk, Maja Taseska, & Emanuël A. P. Habets. (2014). Extended Kalman filter with probabilistic data association for multiple non-concurrent speaker localization in reverberant environments. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 7445–7449. 3 indexed citations
12.
Kowalczyk, Konrad, et al.. (2014). Spatial perception of virtual X-Y recordings. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 22. 129–133. 1 indexed citations
13.
Kowalczyk, Konrad, Emanuël A. P. Habets, Walter Kellermann, & Patrick A. Naylor. (2013). Blind System Identification Using Sparse Learning for TDOA Estimation of Room Reflections. IEEE Signal Processing Letters. 20(7). 653–656. 30 indexed citations
14.
Mabande, Edwin, Konrad Kowalczyk, Haohai Sun, & Walter Kellermann. (2013). Room geometry inference based on spherical microphone array eigenbeam processing. The Journal of the Acoustical Society of America. 134(4). 2773–2789. 22 indexed citations
15.
Antonacci, Fabio, Paolo Bestagini, Alessio Brutti, et al.. (2011). The SCENIC Project: Space-Time Audio Processing for Environment-Aware Acoustic Sensingand Rendering. Journal of the Audio Engineering Society. 13 indexed citations
16.
Kowalczyk, Konrad & Maarten van Walstijn. (2010). A comparison of nonstaggered compact FDTD schemes for the 3D wave equation. Research Portal (Queen's University Belfast). 197–200. 9 indexed citations
17.
Kowalczyk, Konrad, Maarten van Walstijn, & Damian Murphy. (2010). A Phase Grating Approach to Modeling Surface Diffusion in FDTD Room Acoustics Simulations. IEEE Transactions on Audio Speech and Language Processing. 19(3). 528–537. 8 indexed citations
18.
Kowalczyk, Konrad & Ferdinand Svaricek. (2005). EXPERIMENTAL ROBUSTNESS OF FXLMS AND DISTURBANCE-OBSERVER ALGORITHMS FOR ACTIVE VIBRATION CONTROL IN AUTOMOTIVE APPLICATIONS. IFAC Proceedings Volumes. 38(1). 43–48. 2 indexed citations
19.
Kowalczyk, Konrad, et al.. (2004). An Overview of Recent Automotive Applications of Active Vibration Control. Defense Technical Information Center (DTIC). 5 indexed citations
20.
Bøhn, Christian, et al.. (2003). Active control of engine-induced vibrations in automotive vehicles using disturbance observer gain scheduling. Control Engineering Practice. 12(8). 1029–1039. 90 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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