Tugba Erpek

2.5k total citations
56 papers, 1.2k citations indexed

About

Tugba Erpek is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Computer Networks and Communications. According to data from OpenAlex, Tugba Erpek has authored 56 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Artificial Intelligence, 30 papers in Electrical and Electronic Engineering and 25 papers in Computer Networks and Communications. Recurrent topics in Tugba Erpek's work include Wireless Signal Modulation Classification (24 papers), Adversarial Robustness in Machine Learning (15 papers) and Wireless Communication Security Techniques (14 papers). Tugba Erpek is often cited by papers focused on Wireless Signal Modulation Classification (24 papers), Adversarial Robustness in Machine Learning (15 papers) and Wireless Communication Security Techniques (14 papers). Tugba Erpek collaborates with scholars based in United States, United Kingdom and China. Tugba Erpek's co-authors include Yalin E. Sagduyu, Yi Shi, Şennur Ulukuş, Kemal Davaslıoğlu, T. Charles Clancy, Timothy J. O’Shea, M. Cenk Gursoy, Brian Kim, Xueyuan Wang and Jason H. Li and has published in prestigious journals such as IEEE Communications Magazine, IEEE Transactions on Wireless Communications and IEEE Internet of Things Journal.

In The Last Decade

Tugba Erpek

50 papers receiving 1.2k citations

Peers

Tugba Erpek

AI

EEE

CNC

AE

SP

Zhijin Zhao China

Xinping Yi United Kingdom

Marwa Chafii United States

Qiyu Hu China

Keith Nolan Ireland

Junsheng Mu China

Jithin Jagannath United States

Minhoe Kim South Korea

Qiao Tian China

Kunal Sankhe United States

Zhijin Zhao China

Tugba Erpek

224 ×0.3

AI

404 ×0.7

EEE

530 ×1.0

CNC

145 ×0.6

AE

189 ×1.2

SP

Citations per year, relative to Tugba Erpek Tugba Erpek (= 1×) peers Zhijin Zhao

Countries citing papers authored by Tugba Erpek

Since Specialization

Citations

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

Fields of papers citing papers by Tugba Erpek

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tugba Erpek

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Sagduyu, Yalin E., et al.. (2025). Distributed Federated Learning for Vehicular Network Security: Anomaly Detection Benefits and Multi-Domain Attack Threats. 26–31.

2.

Erpek, Tugba, et al.. (2025). How to Combat Reactive and Dynamic Jamming Attacks with Reinforcement Learning. 509–514.

3.

Sagduyu, Yalin E. & Tugba Erpek. (2025). Adversarial Attack and Defense for LoRa Device Identification and Authentication via Deep Learning. IEEE Internet of Things Journal. 12(12). 20261–20271.

4.

Sagduyu, Yalin E., Tugba Erpek, Aylin Yener, & Şennur Ulukuş. (2024). Will 6G Be Semantic Communications? Opportunities and Challenges From Task Oriented and Secure Communications to Integrated Sensing. IEEE Network. 38(6). 72–80. 9 indexed citations

5.

Sagduyu, Yalin E., Tugba Erpek, Aylin Yener, & Şennur Ulukuş. (2024). Joint Sensing and Task-Oriented Communications with Image and Wireless Data Modalities for Dynamic Spectrum Access. 57–62. 3 indexed citations

6.

Davaslıoğlu, Kemal, et al.. (2024). I-SCOUT: Integrated Sensing and Communications to Uncover Moving Targets in NextG Networks. 1–6.

7.

Davaslıoğlu, Kemal, et al.. (2024). Continual Deep Reinforcement Learning to Prevent Catastrophic Forgetting in Jamming Mitigation. 740–745. 2 indexed citations

8.

Sagduyu, Yalin E., Tugba Erpek, Aylin Yener, & Şennur Ulukuş. (2023). Multi - Receiver Task-Oriented Communications via Multi - Task Deep Learning. 1–6. 10 indexed citations

9.

Sagduyu, Yalin E., Tugba Erpek, Şennur Ulukuş, & Aylin Yener. (2023). Vulnerabilities of Deep Learning-Driven Semantic Communications to Backdoor (Trojan) Attacks. 1–6. 15 indexed citations

10.

Sagduyu, Yalin E., Tugba Erpek, & Yi Shi. (2023). Securing NextG Systems against Poisoning Attacks on Federated Learning: A Game-Theoretic Solution. 815–820. 1 indexed citations

11.

Shi, Yi, Yalin E. Sagduyu, Tugba Erpek, & M. Cenk Gursoy. (2022). Jamming Attacks on NextG Radio Access Network Slicing with Reinforcement Learning. 397–402. 8 indexed citations

12.

Shi, Yi, Yalin E. Sagduyu, & Tugba Erpek. (2022). Federated learning for distributed spectrum sensing in NextG communication networks. 59–59. 9 indexed citations

13.

Kim, Brian, Yalin E. Sagduyu, Kemal Davaslıoğlu, Tugba Erpek, & Şennur Ulukuş. (2022). Adversarial Machine Learning for NextG Covert Communications Using Multiple Antennas. Entropy. 24(8). 1047–1047. 3 indexed citations

14.

Wang, Xueyuan, M. Cenk Gursoy, Tugba Erpek, & Yalin E. Sagduyu. (2021). Jamming-Resilient Path Planning for Multiple UAVs via Deep Reinforcement Learning. 1–6. 11 indexed citations

15.

Kim, Brian, Yalin E. Sagduyu, Kemal Davaslıoğlu, Tugba Erpek, & Şennur Ulukuş. (2020). How to Make 5G Communications "Invisible": Adversarial Machine Learning for Wireless Privacy. 763–767. 20 indexed citations

16.

Shi, Yi, Yalin E. Sagduyu, & Tugba Erpek. (2020). Reinforcement Learning for Dynamic Resource Optimization in 5G Radio Access Network Slicing. 1–6. 54 indexed citations

17.

Bhanu, Bir, Tugba Erpek, Yik‐Kiong Hue, et al.. (2020). Integrating deep learning-based data driven and model-based approaches for inverse synthetic aperture radar target recognition. Optical Engineering. 59(5). 1–1. 12 indexed citations

18.

Shi, Yi, Tugba Erpek, Yalin E. Sagduyu, & Jason H. Li. (2018). Spectrum Data Poisoning with Adversarial Deep Learning. 407–412. 45 indexed citations

19.

Shi, Yi, Yalin E. Sagduyu, Tugba Erpek, et al.. (2018). Adversarial Deep Learning for Cognitive Radio Security: Jamming Attack and Defense Strategies. 1–6. 76 indexed citations

20.

O’Shea, Timothy J., Tamoghna Roy, & Tugba Erpek. (2017). Spectral detection and localization of radio events with learned convolutional neural features. 331–335. 22 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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