Boris Karanov

783 total citations
21 papers, 510 citations indexed

About

Boris Karanov is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Boris Karanov has authored 21 papers receiving a total of 510 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Electrical and Electronic Engineering, 11 papers in Artificial Intelligence and 4 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Boris Karanov's work include Optical Network Technologies (18 papers), Advanced Photonic Communication Systems (13 papers) and Wireless Signal Modulation Classification (7 papers). Boris Karanov is often cited by papers focused on Optical Network Technologies (18 papers), Advanced Photonic Communication Systems (13 papers) and Wireless Signal Modulation Classification (7 papers). Boris Karanov collaborates with scholars based in United Kingdom, Netherlands and Germany. Boris Karanov's co-authors include Laurent Schmalen, Polina Bayvel, Domaniç Lavery, Mathieu Chagnon, Tobias A. Eriksson, Félix Thouin, H. Bülow, J. R. Hayes, Gabriele Liga and Lídia Galdino and has published in prestigious journals such as Scientific Reports, Optics Express and IEEE Access.

In The Last Decade

Boris Karanov

18 papers receiving 489 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Boris Karanov United Kingdom 8 464 193 62 23 19 21 510
Rasmus T. Jones Denmark 9 477 1.0× 130 0.7× 128 2.1× 25 1.1× 16 0.8× 21 535
Yoshihisa Inada Japan 15 729 1.6× 240 1.2× 112 1.8× 17 0.7× 33 1.7× 65 759
Sofien Mhatli Tunisia 12 393 0.8× 49 0.3× 94 1.5× 17 0.7× 29 1.5× 44 416
Zhiquan Wan China 11 346 0.7× 77 0.4× 55 0.9× 24 1.0× 32 1.7× 36 382
Mutsam A. Jarajreh United Kingdom 10 330 0.7× 82 0.4× 91 1.5× 25 1.1× 11 0.6× 24 393
Tianwai Bo South Korea 15 584 1.3× 57 0.3× 115 1.9× 18 0.8× 17 0.9× 57 598
Tomáš Horváth Czechia 11 357 0.8× 57 0.3× 102 1.6× 19 0.8× 38 2.0× 109 454
Júlio C. M. Diniz Brazil 9 335 0.7× 48 0.2× 51 0.8× 18 0.8× 16 0.8× 31 365
Wolfgang Schairer Germany 10 334 0.7× 76 0.4× 65 1.0× 20 0.9× 20 1.1× 28 375
Christian Bluemm Germany 13 267 0.6× 55 0.3× 36 0.6× 23 1.0× 48 2.5× 29 298

Countries citing papers authored by Boris Karanov

Since Specialization
Citations

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

Fields of papers citing papers by Boris Karanov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Boris Karanov

This figure shows the co-authorship network connecting the top 25 collaborators of Boris Karanov. A scholar is included among the top collaborators of Boris Karanov 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 Boris Karanov. Boris Karanov 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.
Karanov, Boris, et al.. (2024). On the Robustness of Deep Learning-Aided Symbol Detectors to Varying Conditions and Imperfect Channel Knowledge. TU/e Research Portal. 1–6. 1 indexed citations
2.
Karanov, Boris. (2024). Invited paper: Towards robust end-to-end neural network-based transceivers for short reach fiber links. Optical Fiber Technology. 90. 104069–104069. 1 indexed citations
3.
4.
5.
Karanov, Boris, Gabriele Liga, Olga Vassilieva, et al.. (2022). Hybrid Geometric and Probabilistic Shaping; Is It Really Necessary?. TU/e Research Portal. SpTu1J.4–SpTu1J.4. 2 indexed citations
6.
Karanov, Boris, Laurent Schmalen, & Alex Alvarado. (2021). Distance-Agnostic Auto-Encoders for Short Reach Fiber Communications. Tu5D.1–Tu5D.1. 7 indexed citations
7.
Ferreira, Filipe, Eric Sillekens, Boris Karanov, & Robert I. Killey. (2020). Digital Back Propagation via Sub-Band Processing in Spatial Multiplexing Systems. Journal of Lightwave Technology. 39(4). 1020–1026. 2 indexed citations
8.
Karanov, Boris, Polina Bayvel, & Laurent Schmalen. (2020). End-to-End Learning in Optical Fiber Communications: Concept and Transceiver Design. TU/e Research Portal. 1–4. 7 indexed citations
9.
Karanov, Boris, Mathieu Chagnon, Vahid Aref, et al.. (2020). Optical Fiber Communication Systems Based on End-to-End Deep Learning : (Invited Paper). 1–2. 5 indexed citations
10.
Sillekens, Eric, Daniel Semrau, Boris Karanov, et al.. (2020). Time-Domain Learned Digital Back-Propagation. 1–4. 5 indexed citations
11.
Karanov, Boris, Gabriele Liga, Vahid Aref, et al.. (2019). Deep Learning for Communication over Dispersive Nonlinear Channels:\n Performance and Comparison with Classical Digital Signal Processing. arXiv (Cornell University). 11 indexed citations
12.
Karanov, Boris, Domaniç Lavery, Polina Bayvel, & Laurent Schmalen. (2019). End-to-End Optimized Transmission over Dispersive Intensity-modulated Channels Using Bidirectional Recurrent Neural Networks. Repository KITopen (Karlsruhe Institute of Technology). 66 indexed citations
13.
Karanov, Boris, Mathieu Chagnon, Félix Thouin, et al.. (2018). End-to-End Deep Learning of Optical Fiber Communications. Journal of Lightwave Technology. 36(20). 4843–4855. 279 indexed citations
14.
Liu, Zhixin, M. N. Petrovich, David J. Richardson, et al.. (2018). Nonlinearity-Free Coherent Transmission in Hollow-Core Antiresonant Fiber. Journal of Lightwave Technology. 37(3). 909–916. 61 indexed citations
15.
Karanov, Boris, Tianhua Xu, Nikita A. Shevchenko, et al.. (2018). Digital Nonlinearity Compensation Considering Signal Spectral Broadening Effects in Dispersion-managed Systems. Optical Fiber Communication Conference. W2A.58–W2A.58.
16.
Chagnon, Mathieu, Boris Karanov, & Laurent Schmalen. (2018). Experimental Demonstration of a Dispersion Tolerant End-to-End Deep Learning-Based IM-DD Transmission System. 1–3. 22 indexed citations
17.
Karanov, Boris, Tianhua Xu, Nikita A. Shevchenko, et al.. (2017). Span length and information rate optimisation in optical transmission systems using single-channel digital backpropagation. Optics Express. 25(21). 25353–25353. 9 indexed citations
18.
Xu, Tianhua, Boris Karanov, Nikita A. Shevchenko, et al.. (2017). Digital nonlinearity compensation in high-capacity optical communication systems considering signal spectral broadening effect. Scientific Reports. 7(1). 12986–12986. 15 indexed citations
19.
Liu, Zhixin, Lídia Galdino, J. R. Hayes, et al.. (2017). Record High Capacity (6.8 Tbit/s) WDM Coherent Transmission in Hollow-Core Antiresonant Fiber. ePrints Soton (University of Southampton). Th5B.8–Th5B.8. 7 indexed citations
20.
Xu, Tianhua, Nikita A. Shevchenko, Boris Karanov, et al.. (2017). Nonlinearity Compensation and Information Rates in Fully-Loaded C-band Optical Fibre Transmission Systems. Warwick Research Archive Portal (University of Warwick). 1–3.

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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