Noa Zilberman

2.4k total citations
66 papers, 1.3k citations indexed

About

Noa Zilberman is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Information Systems. According to data from OpenAlex, Noa Zilberman has authored 66 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Computer Networks and Communications, 25 papers in Electrical and Electronic Engineering and 15 papers in Information Systems. Recurrent topics in Noa Zilberman's work include Software-Defined Networks and 5G (37 papers), Interconnection Networks and Systems (19 papers) and Advanced Optical Network Technologies (16 papers). Noa Zilberman is often cited by papers focused on Software-Defined Networks and 5G (37 papers), Interconnection Networks and Systems (19 papers) and Advanced Optical Network Technologies (16 papers). Noa Zilberman collaborates with scholars based in United Kingdom, Israel and United States. Noa Zilberman's co-authors include Andrew W. Moore, Yuval Shavitt, Yury Audzevich, G. Adam Covington, Changgang Zheng, Robert Soulé, Nick McKeown, Fernando Pedone, Huynh Tu Dang and Gordon Brebner and has published in prestigious journals such as Science, Proceedings of the IEEE and IEEE Communications Surveys & Tutorials.

In The Last Decade

Noa Zilberman

58 papers receiving 1.2k citations

Peers

Noa Zilberman
Benoît Donnet Belgium
Marco Chiesa Sweden
Ranjita Bhagwan United States
Y. C. Tay Singapore
Chin‐Tser Huang United States
Xiaozhou Li Finland
Roman Vitenberg Norway
Joseph Pasquale United States
Peter Van Roy Belgium
Benoît Donnet Belgium
Noa Zilberman
Citations per year, relative to Noa Zilberman Noa Zilberman (= 1×) peers Benoît Donnet

Countries citing papers authored by Noa Zilberman

Since Specialization
Citations

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

Fields of papers citing papers by Noa Zilberman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Noa Zilberman

This figure shows the co-authorship network connecting the top 25 collaborators of Noa Zilberman. A scholar is included among the top collaborators of Noa Zilberman 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 Noa Zilberman. Noa Zilberman 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.
Zilberman, Noa, et al.. (2025). Carbon-Intelligent Content Scheduling in CDNs. 1–8.
2.
3.
Zheng, Changgang, et al.. (2024). Planter: Rapid Prototyping of In-Network Machine Learning Inference. ACM SIGCOMM Computer Communication Review. 54(1). 2–21. 14 indexed citations
4.
Zheng, Changgang, et al.. (2024). IIsy: Hybrid In-Network Classification Using Programmable Switches. IEEE/ACM Transactions on Networking. 32(3). 2555–2570. 21 indexed citations
5.
Zheng, Changgang, et al.. (2024). Federated In-Network Machine Learning for Privacy-Preserving IoT Traffic Analysis. ACM Transactions on Internet Technology. 24(4). 1–24.
6.
Zheng, Changgang, et al.. (2023). DINC: Toward Distributed In-Network Computing. 1(CoNEXT3). 1–25. 13 indexed citations
7.
Zheng, Changgang, et al.. (2023). Toward Continuous Threat Defense: in-Network Traffic Analysis for IoT Gateways. IEEE Internet of Things Journal. 11(6). 9244–9257. 14 indexed citations
8.
Zheng, Changgang, et al.. (2023). QCMP. 35–40. 8 indexed citations
9.
Zheng, Changgang, et al.. (2023). In-Network Machine Learning Using Programmable Network Devices: A Survey. IEEE Communications Surveys & Tutorials. 26(2). 1171–1200. 27 indexed citations
10.
Zilberman, Noa, Eve M. Schooler, Uri Cummings, et al.. (2023). Toward Carbon-Aware Networking. 3(3). 15–20. 7 indexed citations
11.
Armour, Wesley, et al.. (2022). Network-accelerated cluster scheduler. 16–18.
12.
Zilberman, Noa, et al.. (2020). Finding hard-to-find data plane bugs with a PTA. Oxford University Research Archive (ORA) (University of Oxford). 218–231. 9 indexed citations
13.
Zilberman, Noa. (2020). An Artifact Evaluation of NDP, Dataset. Oxford University Research Archive (ORA) (University of Oxford). 1 indexed citations
14.
Dang, Huynh Tu, et al.. (2019). The Case For In-Network Computing On Demand. Apollo (University of Cambridge). 1–16. 72 indexed citations
15.
Zilberman, Noa, et al.. (2019). Stardust: Divide and Conquer in the Data Center Network. Apollo (University of Cambridge). 141–159. 12 indexed citations
16.
Matsutani, Hiroki, et al.. (2018). LaKe: The Power of In-Network Computing. Apollo (University of Cambridge). 1–8. 26 indexed citations
17.
Greaves, David, Marcin Wójcik, Richard G. Clegg, et al.. (2017). Emu: Rapid Prototyping of Networking Services. Apollo (University of Cambridge). 459–471. 18 indexed citations
18.
Zilberman, Noa, Andrew W. Moore, & Jon Crowcroft. (2016). From photons to big-data applications: terminating terabits. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 374(2062). 20140445–20140445. 6 indexed citations
19.
Zilberman, Noa, Yury Audzevich, G. Adam Covington, & Andrew W. Moore. (2014). NetFPGA SUME: Toward Research Commodity 100Gb/s. 4 indexed citations
20.
Koenigstein, Noam, Yuval Shavitt, & Noa Zilberman. (2009). Predicting Billboard Success Using Data-Mining in P2P Networks. 465–470. 13 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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