Sergey Serebryakov

413 total citations
31 papers, 215 citations indexed

About

Sergey Serebryakov is a scholar working on Artificial Intelligence, Computer Networks and Communications and Electrical and Electronic Engineering. According to data from OpenAlex, Sergey Serebryakov has authored 31 papers receiving a total of 215 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 8 papers in Computer Networks and Communications and 7 papers in Electrical and Electronic Engineering. Recurrent topics in Sergey Serebryakov's work include Advanced Memory and Neural Computing (7 papers), Peer-to-Peer Network Technologies (5 papers) and Ferroelectric and Negative Capacitance Devices (4 papers). Sergey Serebryakov is often cited by papers focused on Advanced Memory and Neural Computing (7 papers), Peer-to-Peer Network Technologies (5 papers) and Ferroelectric and Negative Capacitance Devices (4 papers). Sergey Serebryakov collaborates with scholars based in United States, Russia and Germany. Sergey Serebryakov's co-authors include John Paul Strachan, Catherine E. Graves, Can Li, Martin Foltín, Giacomo Pedretti, Xia Sheng, Dejan Milojičić, Phil Laplante, Vladimir Gorodetsky and Thomas Van Vaerenbergh and has published in prestigious journals such as Computer, Advanced Electronic Materials and IEEE Internet Computing.

In The Last Decade

Sergey Serebryakov

25 papers receiving 202 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sergey Serebryakov United States 7 96 80 35 25 21 31 215
Shamik Kundu United States 9 143 1.5× 85 1.1× 36 1.0× 22 0.9× 87 4.1× 38 249
Matthew Cotter United States 13 328 3.4× 96 1.2× 41 1.2× 85 3.4× 38 1.8× 24 415
Shaojun Wei China 9 132 1.4× 53 0.7× 80 2.3× 43 1.7× 90 4.3× 32 244
Fangyang Shen United States 11 158 1.6× 106 1.3× 119 3.4× 11 0.4× 11 0.5× 38 318
Minxuan Zhou United States 10 239 2.5× 97 1.2× 71 2.0× 67 2.7× 84 4.0× 35 332
Bappaditya Dey Belgium 10 135 1.4× 55 0.7× 14 0.4× 45 1.8× 24 1.1× 48 238
Da Li United States 7 69 0.7× 142 1.8× 56 1.6× 59 2.4× 47 2.2× 17 280
Biresh Kumar Joardar United States 12 230 2.4× 103 1.3× 101 2.9× 80 3.2× 89 4.2× 39 332

Countries citing papers authored by Sergey Serebryakov

Since Specialization
Citations

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

Fields of papers citing papers by Sergey Serebryakov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sergey Serebryakov

This figure shows the co-authorship network connecting the top 25 collaborators of Sergey Serebryakov. A scholar is included among the top collaborators of Sergey Serebryakov 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 Sergey Serebryakov. Sergey Serebryakov 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.
Mansurova, Madina, et al.. (2025). Enhancing U-Net Segmentation Accuracy Through Comprehensive Data Preprocessing. Journal of Imaging. 11(2). 50–50. 1 indexed citations
2.
3.
Serebryakov, Sergey, et al.. (2025). Constructing a metadata knowledge graph as an atlas for demystifying AI pipeline optimization. Frontiers in Big Data. 7. 1476506–1476506. 2 indexed citations
4.
5.
Pedretti, Giacomo, Sergey Serebryakov, Omar Eldash, et al.. (2024). CAMSHAP: Accelerating Machine Learning Model Explainability with Analog CAM. 1–9.
6.
Pedretti, Giacomo, Sergey Serebryakov, Ron M. Roth, et al.. (2024). X-TIME: Accelerating Large Tree Ensembles Inference for Tabular Data With Analog CAMs. IEEE Journal on Exploratory Solid-State Computational Devices and Circuits. 10. 116–124. 2 indexed citations
7.
Serebryakov, Sergey, et al.. (2024). Common Metadata Framework: Integrated Framework for Trustworthy Artificial Intelligence Pipelines. IEEE Internet Computing. 28(3). 37–44. 2 indexed citations
8.
Serebryakov, Sergey, et al.. (2024). AIOps and Sustainability: Transforming Data Centers for a Greener Future. 1867–1871.
9.
Pedretti, Giacomo, Fabian Böhm, Tanmoy Bhattacharya, et al.. (2023). Zeroth and higher-order logic with content addressable memories. 1–4. 3 indexed citations
10.
Serebryakov, Sergey, et al.. (2022). Information Support for Management Tasks in the Conditions of Digital Transformation. Interexpo GEO-Siberia. 1. 86–92.
11.
Pedretti, Giacomo, Catherine E. Graves, Can Li, et al.. (2021). Tree-based machine learning performed in-memory with memristive analog CAM. arXiv (Cornell University). 78 indexed citations
12.
Huang, Sitao, Aayush Ankit, Sai Rahul Chalamalasetti, et al.. (2021). Mixed Precision Quantization for ReRAM-based DNN Inference Accelerators. 372–377. 24 indexed citations
13.
Laplante, Phil, et al.. (2020). Artificial Intelligence and Critical Systems: From Hype to Reality. Computer. 53(11). 45–52. 19 indexed citations
14.
Huang, Xinyuan, et al.. (2019). Benchmarking Deep Learning for Time Series: Challenges and Directions. 5679–5682. 8 indexed citations
15.
Serebryakov, Sergey, et al.. (2017). Geo-Information Technology of 8-Level Responsibility: Concept and Standard of Construction Management for Implementation of The BIM-Technology in Russia. IOP Conference Series Earth and Environmental Science. 95. 42007–42007. 1 indexed citations
16.
Gorodetsky, Vladimir, et al.. (2010). Ontology - Based Context - Dependent Personalization Technology.. 278–283. 2 indexed citations
17.
Gorodetsky, Vladimir, et al.. (2008). Interaction of Agents and Data Mining in Ubiquitous Environment. 562–566. 5 indexed citations
18.
Gorodetsky, Vladimir, et al.. (2007). Automated P2P Learning in Agent-Based Classification Networks. 503–507. 2 indexed citations
19.
Serebryakov, Sergey, et al.. (2006). Agent-based Service-Oriented Intelligent P2P Networks for Distributed Classification. 224–233. 7 indexed citations
20.
Serebryakov, Sergey, et al.. (2006). Agent-based Service-Oriented Intelligent P2P Networks for Distributed Classification. 2. 224–233. 5 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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