Eliya Nachmani

1.1k total citations · 1 hit paper
10 papers, 468 citations indexed

About

Eliya Nachmani is a scholar working on Artificial Intelligence, Computer Networks and Communications and Signal Processing. According to data from OpenAlex, Eliya Nachmani has authored 10 papers receiving a total of 468 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 3 papers in Computer Networks and Communications and 3 papers in Signal Processing. Recurrent topics in Eliya Nachmani's work include Speech Recognition and Synthesis (4 papers), Error Correcting Code Techniques (3 papers) and Speech and Audio Processing (2 papers). Eliya Nachmani is often cited by papers focused on Speech Recognition and Synthesis (4 papers), Error Correcting Code Techniques (3 papers) and Speech and Audio Processing (2 papers). Eliya Nachmani collaborates with scholars based in Israel, United States and United Kingdom. Eliya Nachmani's co-authors include Y. Be'ery, Loren Lugosch, David Burshtein, Warren J. Gross, Lior Wolf, Yossi Adi, Nitzan Shahar, Heiga Zen, Jia Ye and Nadav Bar and has published in prestigious journals such as PLoS Computational Biology, IEEE Communications Letters and IEEE Journal of Selected Topics in Signal Processing.

In The Last Decade

Eliya Nachmani

9 papers receiving 454 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Deep Learning Methods for Improved Decoding of Linear Codes

2018 344 citations Eliya Nachmani, Loren Lugosch et al. IEEE Journal of Selected Topics in Signal Processing profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Eliya Nachmani Israel	7	291	250	209	118	63	10	468
Tarik Kazaz Netherlands	8	209 0.7×	198 0.8×	114 0.5×	59 0.5×	24 0.4×	15	390
Sajjad Ahmed Ghauri Pakistan	11	134 0.5×	167 0.7×	117 0.6×	34 0.3×	59 0.9×	39	354
Fei Liang China	6	172 0.6×	327 1.3×	183 0.9×	51 0.4×	27 0.4×	12	445
Roland Gautier France	10	121 0.4×	175 0.7×	192 0.9×	94 0.8×	24 0.4×	34	300
Sebastian Dörner Germany	7	410 1.4×	485 1.9×	137 0.7×	97 0.8×	39 0.6×	15	685
Mikołaj Jankowski United Kingdom	7	202 0.7×	197 0.8×	104 0.5×	35 0.3×	15 0.2×	9	446
Ihsan Akbar United States	4	171 0.6×	266 1.1×	390 1.9×	147 1.2×	12 0.2×	6	541
Hsiao-Chun Wu United States	7	309 1.1×	96 0.4×	75 0.4×	123 1.0×	131 2.1×	15	387
Wan-Ting Shih Taiwan	7	313 1.1×	651 2.6×	121 0.6×	75 0.6×	29 0.5×	11	827
T. Yucek United States	12	89 0.3×	535 2.1×	497 2.4×	63 0.5×	22 0.3×	19	656

Countries citing papers authored by Eliya Nachmani

Since Specialization

Citations

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

Fields of papers citing papers by Eliya Nachmani

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eliya Nachmani

This figure shows the co-authorship network connecting the top 25 collaborators of Eliya Nachmani. A scholar is included among the top collaborators of Eliya Nachmani 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 Eliya Nachmani. Eliya Nachmani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

1.

Nachmani, Eliya, et al.. (2025). SimulTron: On-Device Simultaneous Speech to Speech Translation. 1–5.

2.

Nachmani, Eliya, et al.. (2024). Harnessing the flexibility of neural networks to predict dynamic theoretical parameters underlying human choice behavior. PLoS Computational Biology. 20(1). e1011678–e1011678. 6 indexed citations

3.

Nachmani, Eliya, et al.. (2024). Translatotron 3: Speech to Speech Translation with Monolingual Data. 10686–10690. 4 indexed citations

4.

Nachmani, Eliya, et al.. (2022). Zero-Shot Voice Conditioning for Denoising Diffusion TTS Models. Interspeech 2022. 2983–2987. 16 indexed citations

5.

Nachmani, Eliya, et al.. (2022). SepIt: Approaching a Single Channel Speech Separation Bound. Interspeech 2022. 5323–5327. 17 indexed citations

6.

Nachmani, Eliya & Y. Be'ery. (2022). Neural Decoding With Optimization of Node Activations. IEEE Communications Letters. 26(11). 2527–2531. 11 indexed citations

7.

Nachmani, Eliya, et al.. (2021). Recovering AES Keys with a Deep Cold Boot Attack. arXiv (Cornell University). 12955–12966. 1 indexed citations

8.

Nachmani, Eliya, Yossi Adi, & Lior Wolf. (2020). Voice Separation with an Unknown Number of Multiple Speakers. International Conference on Machine Learning. 1. 7164–7175. 58 indexed citations

9.

Nachmani, Eliya & Lior Wolf. (2019). Hyper-Graph-Network Decoders for Block Codes. arXiv (Cornell University). 32. 2326–2336. 11 indexed citations

10.

Nachmani, Eliya, et al.. (2018). Deep Learning Methods for Improved Decoding of Linear Codes. IEEE Journal of Selected Topics in Signal Processing. 12(1). 119–131. 344 indexed citations breakdown →

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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