Berk Canberk

2.6k total citations · 1 hit paper
147 papers, 1.6k citations indexed

About

Berk Canberk is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Aerospace Engineering. According to data from OpenAlex, Berk Canberk has authored 147 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 99 papers in Computer Networks and Communications, 70 papers in Electrical and Electronic Engineering and 31 papers in Aerospace Engineering. Recurrent topics in Berk Canberk's work include Software-Defined Networks and 5G (27 papers), Advanced MIMO Systems Optimization (27 papers) and IoT and Edge/Fog Computing (26 papers). Berk Canberk is often cited by papers focused on Software-Defined Networks and 5G (27 papers), Advanced MIMO Systems Optimization (27 papers) and IoT and Edge/Fog Computing (26 papers). Berk Canberk collaborates with scholars based in Türkiye, United Kingdom and United States. Berk Canberk's co-authors include Trung Q. Duong, Tuğçe Bilen, Kaushik Chowdhury, Octavia A. Dobre, Gökhan Seçinti, Sema Oktuğ, Vishal Sharma, Ian F. Akyildiz, Muhammad Fahim and Dang Van Huynh and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Access.

In The Last Decade

Berk Canberk

128 papers receiving 1.6k citations

Hit Papers

Advancing 6G: Survey for Explainable AI on Communications... 2025 2026 2025 5 10 15 20 25

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Berk Canberk Türkiye 21 1.0k 847 282 256 142 147 1.6k
Νικόλαος Νομικός Greece 20 833 0.8× 1.1k 1.3× 490 1.7× 123 0.5× 82 0.6× 87 1.7k
Mushu Li Canada 18 1.1k 1.0× 890 1.1× 202 0.7× 92 0.4× 196 1.4× 56 1.8k
Lun Tang China 20 1.7k 1.7× 1.0k 1.2× 169 0.6× 142 0.6× 417 2.9× 93 2.1k
Daniele Tarchi Italy 23 1.4k 1.3× 1.1k 1.3× 492 1.7× 55 0.2× 221 1.6× 152 1.9k
Tiago Koketsu Rodrigues Japan 18 922 0.9× 591 0.7× 243 0.9× 78 0.3× 293 2.1× 32 1.4k
Shuo Wang China 17 1.1k 1.0× 789 0.9× 158 0.6× 51 0.2× 300 2.1× 127 1.7k
Haijun Liao China 21 1.0k 1.0× 804 0.9× 187 0.7× 94 0.4× 313 2.2× 56 1.7k
Qingyang Song China 25 1.5k 1.4× 1.4k 1.6× 259 0.9× 42 0.2× 126 0.9× 112 2.0k
Yi Zhong China 20 660 0.6× 787 0.9× 77 0.3× 204 0.8× 99 0.7× 88 1.3k

Countries citing papers authored by Berk Canberk

Since Specialization
Citations

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

Fields of papers citing papers by Berk Canberk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Berk Canberk

This figure shows the co-authorship network connecting the top 25 collaborators of Berk Canberk. A scholar is included among the top collaborators of Berk Canberk 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 Berk Canberk. Berk Canberk 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.
Huynh, Dang Van, Saeed R. Khosravirad, Vishal Sharma, et al.. (2025). Carbon-Aware Edge Computing for Internet of Everything Networks: A Digital Twin Approach. IEEE Internet of Things Journal. 12(15). 29240–29251.
2.
Μαγλαράς, Λέανδρος, et al.. (2025). Black Hole Prediction in Backbone Networks: A Comprehensive and Type-Independent Forecasting Model. IEEE Transactions on Network and Service Management. 22(5). 4983–4997.
3.
Narottama, Bhaskara, James Adu Ansere, Nidhi Simmons, et al.. (2025). Quantum Deep Reinforcement Learning for Digital Twin-Enabled 6G Networks and Semantic Communications: Considerations for Adoption and Security. IEEE Transactions on Network Science and Engineering. 13. 2053–2076. 1 indexed citations
5.
Liu, Yifan, et al.. (2025). Advancing 6G: Survey for Explainable AI on Communications and Network Slicing. IEEE Open Journal of the Communications Society. 6. 1372–1412. 25 indexed citations breakdown →
6.
Cheema, Adnan Ahmad, et al.. (2025). Channel Estimation for Reconfigurable Intelligent Surface-Aided 6G NOMA Systems: A Quantum Machine Learning Approach. IEEE Transactions on Network Science and Engineering. 13. 2197–2218.
7.
Huynh, Dang Van, et al.. (2025). Quantum Deep Reinforcement Learning for URLLC Satellite-Air-Ground Integrated Networks With Digital Twin Applications. IEEE Internet of Things Journal. 13(3). 4230–4246.
8.
Canberk, Berk, et al.. (2024). Digital Twin-Empowered Integrated Satellite-Terrestrial Networks Toward 6G Internet of Things. IEEE Communications Magazine. 62(12). 74–81. 5 indexed citations
9.
Canberk, Berk, et al.. (2024). What-if Analysis Framework for Digital Twins in 6G Wireless Network Management. Istanbul Technical University Academic Open Archive (Istanbul Technical University). 232–237. 8 indexed citations
10.
Μαγλαράς, Λέανδρος, et al.. (2024). AI-Enhanced Digital Twin Framework for Cyber-Resilient 6G Internet of Vehicles Networks. IEEE Internet of Things Journal. 11(22). 36168–36181. 22 indexed citations
11.
Μαγλαράς, Λέανδρος, et al.. (2024). Cyber-Twin: Digital Twin-Boosted Autonomous Attack Detection for Vehicular Ad-Hoc Networks. 2167–2172. 9 indexed citations
12.
Canberk, Berk, et al.. (2024). Intelligent Digital Twin Communication Framework for Addressing Accuracy and Timeliness Tradeoff in Resource-Constrained Networks. IEEE Transactions on Cognitive Communications and Networking. 11(3). 1954–1965. 3 indexed citations
13.
Canberk, Berk, et al.. (2024). Generative AI-enabled Digital Twins for 6G-enhanced Smart Cities. Edinburgh Napier Research Repository (Edinburgh Napier University). 1–6. 1 indexed citations
14.
Chrysoulas, Christos, et al.. (2023). Digital Twin-Empowered Smart Attack Detection System for 6G Edge of Things Networks. Edinburgh Napier Research Repository (Edinburgh Napier University). 178–183. 11 indexed citations
15.
Canberk, Berk, et al.. (2023). Opportunistic RL-based WiFi Access for Aerial Sensor Nodes in Smart City Applications. Edinburgh Napier Research Repository (Edinburgh Napier University). 9. 1–5. 1 indexed citations
16.
Canberk, Berk, et al.. (2022). Digital Twin Driven Blockchain Based Reliable and Efficient 6G Edge Network. Istanbul Technical University Academic Open Archive (Istanbul Technical University). 342–348. 10 indexed citations
17.
Canberk, Berk, et al.. (2021). Energy‐aware mobility for aerial networks: A reinforcement learning approach. International Journal of Network Management. 32(1). 4 indexed citations
18.
Naderi, M. Yousof, et al.. (2021). WiFED Mobile: WiFi Friendly Energy Delivery With Mobile Distributed Beamforming. IEEE/ACM Transactions on Networking. 29(3). 1362–1375. 12 indexed citations
19.
Canberk, Berk, et al.. (2020). OFaaS: OpenFlow Switch as a Service for Multi Tenant Slicing in SD-CDN. IEEE Transactions on Network and Service Management. 18(1). 362–373. 12 indexed citations
20.
Canberk, Berk, et al.. (2019). Road to 5G Reduced-Latency: A Software Defined Handover Model for eMBB Services. IEEE Transactions on Vehicular Technology. 68(8). 8133–8144. 30 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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