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Yalin E. Sagduyu

Yalin E. Sagduyu

D-Index & Metrics

Computer Science

D-Index
38
Citations
5464
World Ranking
10329
National Ranking
4329

Overview

Yalin E. Sagduyu is affiliated with Virginia Tech in the United States and has a research focus spanning multiple areas within computer science and engineering. Their publications reflect extensive work in fields such as artificial intelligence, electrical and electronic engineering, and computer networks and communications.

The main research topics addressed by Sagduyu include wireless signal modulation classification, adversarial robustness in machine learning, wireless communication security techniques, network security and intrusion detection, distributed sensor networks and detection algorithms, and bacterial research related to Bacillus and Francisella. Additionally, their work touches on millimeter-wave propagation and modeling.

The scientist has collaborated frequently with several coauthors. Among the most frequent are Tugba Erpek, Şennur Ulukuş, Kemal Davaslıoğlu, Yi Shi, and Aylin Yener. These collaborations have contributed to a diverse set of publications across various scientific venues.

Sagduyu's recent papers illustrate their engagement with advanced topics in wireless communications and adversarial machine learning. Selected papers include:

  • Channel-Aware Adversarial Attacks Against Deep Learning-Based Wireless Signal Classifiers, 2021, IEEE Transactions on Wireless Communications
  • Adversarial Machine Learning in Wireless Communications Using RF Data: A Review, 2022, IEEE Communications Surveys & Tutorials
  • Learning-Based UAV Path Planning for Data Collection With Integrated Collision Avoidance, 2022, IEEE Internet of Things Journal
  • Generative Adversarial Network in the Air: Deep Adversarial Learning for Wireless Signal Spoofing, 2020, IEEE Transactions on Cognitive Communications and Networking
  • When Attackers Meet AI: Learning-Empowered Attacks in Cooperative Spectrum Sensing, 2020, IEEE Transactions on Mobile Computing

Publications are often disseminated through a variety of scientific forums. Among the most frequent publication venues for Sagduyu are:

  • arXiv (Cornell University)
  • MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM)
  • IEEE Internet of Things Journal
  • IEEE Transactions on Cognitive Communications and Networking
  • IEEE Communications Magazine

The composition of Sagduyu's research output is strongly concentrated in computer science with 137 publications and engineering with 77 publications, illustrating a cross-disciplinary approach bridging theoretical and applied research domains.

Best Publications

  • Deep Learning for Launching and Mitigating Wireless Jamming Attacks

    Tugba Erpek;Yalin E. Sagduyu;Yi Shi

  • Jamming games in wireless networks with incomplete information

    Y. E. Sagduyu;R. A. Berry;A. Ephremides

  • Channel-Aware Adversarial Attacks Against Deep Learning-Based Wireless Signal Classifiers

    Brian Kim;Yalin E. Sagduyu;Kemal Davaslioglu;Tugba Erpek

  • Deep Learning for Wireless Communications

    Tugba Erpek;Timothy J. O'Shea;Yalin E. Sagduyu;Yi Shi

  • On Joint MAC and Network Coding in Wireless Ad Hoc Networks

    Y.E. Sagduyu;A. Ephremides

  • Adversarial Deep Learning for Cognitive Radio Security: Jamming Attack and Defense Strategies

    Yi Shi;Yalin E. Sagduyu;Tugba Erpek;Kemal Davaslioglu

  • Deep Learning for RF Signal Classification in Unknown and Dynamic Spectrum Environments

    Yi Shi;Kemal Davaslioglu;Yalin E. Sagduyu;William C. Headley

  • Generative Adversarial Learning for Spectrum Sensing

    Kemal Davaslioglu;Yalin E. Sagduyu

  • Cross-Layer Optimization of MAC and Network Coding in Wireless Queueing Tandem Networks

    Y.E. Sagduyu;A. Ephremides

  • Generative Adversarial Network in the Air: Deep Adversarial Learning for Wireless Signal Spoofing

    Yi Shi;Kemal Davaslioglu;Yalin E. Sagduyu

  • A game-theoretic analysis of denial of service attacks in wireless random access

    Yalin Evren Sagduyu;Anthony Ephremides

  • How to steal a machine learning classifier with deep learning

    Yi Shi;Yalin Sagduyu;Alexander Grushin

  • IoT Network Security from the Perspective of Adversarial Deep Learning

    Yalin E. Sagduyu;Yi Shi;Tugba Erpek

  • The problem of medium access control in wireless sensor networks

    Y.E. Sagduyu;A. Ephremides

  • Adversarial Deep Learning for Over-the-Air Spectrum Poisoning Attacks

    Yalin E. Sagduyu;Yi Shi;Tugba Erpek

  • Generative Adversarial Network for Wireless Signal Spoofing

    Yi Shi;Kemal Davaslioglu;Yalin E. Sagduyu

  • Over-the-Air Adversarial Attacks on Deep Learning Based Modulation Classifier over Wireless Channels

    Brian Kim;Yalin E. Sagduyu;Kemal Davaslioglu;Tugba Erpek

  • MAC games for distributed wireless network security with incomplete information of selfish and malicious user types

    Yalin Evren Sagduyu;Randall Berry;Anthony Ephremides

  • Joint Scheduling and Wireless Network Coding

    Yalin Evren Sagduyu;Anthony Ephremides

  • Spectrum Data Poisoning with Adversarial Deep Learning

    Yi Shi;Tugba Erpek;Yalin E. Sagduyu;Jason H. Li

  • Reinforcement Learning for Dynamic Resource Optimization in 5G Radio Access Network Slicing

    Yi Shi;Yalin E. Sagduyu;Tugba Erpek

  • DeepWiFi: Cognitive WiFi with Deep Learning

    Kemal Davaslioglu;Sohraab Soltani;Tugba Erpek;Yalin E. Sagduyu

Frequent Co-Authors

Yi Shi
Yi Shi Virginia Tech
Anthony Ephremides
Anthony Ephremides University of Maryland, College Park
Sennur Ulukus
Sennur Ulukus University of Maryland, College Park
Junshan Zhang
Junshan Zhang University of California, Davis
Randall A. Berry
Randall A. Berry Northwestern University
Lei Yang
Lei Yang Hong Kong Polytechnic University
Dongning Guo
Dongning Guo Northwestern University
Aylin Yener
Aylin Yener The Ohio State University
Wolfgang Utschick
Wolfgang Utschick Technical University of Munich
Michael L. Honig
Michael L. Honig Northwestern University

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