M. Cenk Gursoy

Professor

3-181 CST

mcgursoy@syr.edu

315.443.4403

Personal Website

Degree(s):

  • Ph.D. , Princeton University, 2004.
  • B.S., Bogazici University, Istanbul, Turkey, 1999.

Lab/ Center/ Institute Affiliations:

Director, Wireless Communication and Networking Lab.

Senior Research Associate and Core Faculty Member, Autonomous Systems Policy Institute

Areas of Expertise:

Wireless Networking

Signal Processing

Communication/Information Theory

Machine Learning

Decision Making Theory

Optimization

Unmanned Systems

Dr. Gursoy has broad research expertise in the general areas of wireless communications and networking, signal processing, information theory, optimization, and machine learning. In particular, he has conducted research in detection and estimation, hypothesis testing, anomaly detection, optimal resource allocation, wireless performance evaluation, cognitive radio networks, dynamic spectrum access, energy efficiency analysis, multiple-antenna communication, millimeter wave communications, low-latency communications, physical-layer security, radio access networks, scheduling, edge computing, content caching, and 4G/5G/beyond-5G wireless network design. His expertise in information theory includes the analysis of wireless channel capacity and optimal signaling and coding schemes. He further has expertise in machine learning through the design, implementation and application of deep learning, reinforcement learning, and federated learning algorithms. Moreover, he has studied sequential optimization and decision-making in highly dynamic scenarios (involving autonomous and unmanned systems), and security and privacy in distributed learning.

Honors and Awards:

  • 2020 IEEE Region 1 Technological Innovation (Academic) Award
  • 2019 The 38th AIAA/IEEE Digital Avionics Systems Conference Best of Session    Award.
  • 2017 IEEE Green Communications & Computing Technical Committee Best Journal Paper Award.
  • 2017 IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) Best Paper Award
  • 2008 EURASIP Journal of Wireless Communications and Networking Best Paper Award
  • NSF CAREER Award

Selected Publications:

  • G. Joseph, C. Zhong, M. C. Gursoy, S. Velipasalar, and P. K. Varshney, “Anomaly Detection via Learning-Based Sequential Controlled Sensing,” IEEE Sensors Journal, vol. 24, no. 13, pp. 21025-21037, July 2024.
  • F. Wang, M. C. Gursoy, and S. Velipasalar, “Feature-based Federated Transfer Learning: Communication Efficiency, Robustness and Privacy,” IEEE Transactions on Machine Learning in Communications and Networking, vol. 2, pp. 823-840, 2024.
  • M. H. Sulieman, M. Liu, F. Kong, and M. C. Gursoy, “Path Planning for UAVs Under GPS Permanent Faults,” ACM Transactions on Cyber-Physical Systems, 2024.
  • X. Li, Z. Tian, W. He, G. Chen, M. C. Gursoy, S. Mumtaz, and A. Nallanathan, “Covert Communication of STAR-RIS Aided NOMA Networks,” IEEE Transactions on Vehicular Technology, vol. 73, no. 6, pp. 9055-9060, June 2024.
  • Y. Yang, Y. Hu, and M. C. Gursoy, “Energy Efficiency of RIS-Assisted NOMA-Based MEC Networks in the Finite Blocklength Regime,” IEEE Transactions on Communications, vol. 72, no. 4, pp. 2275-2291, April 2024.
  • F. Wang, M. C. Gursoy, and S. Velipasalar, “Robust Network Slicing: Multi-Agent Policies, Adversarial Attacks, and Defensive Strategies,” IEEE Transactions on Machine Learning in Communications and Networking, vol. 2, pp. 49-63, 2024.
  • Y. Yang and M. C. Gursoy, “Joint Trajectory Design and Resource Optimization in UAV-assisted Caching-Enabled Networks with Finite Blocklength Transmissions,” Drones, 2024; 8(1):12.
  • Z. Lu and M. C. Gursoy, “Resource Allocation for Multi-target Radar Tracking via Constrained Deep Reinforcement Learning,” IEEE Transactions on Cognitive Communications and Networking, vol. 9, no. 6, pp. 1677-1690, Dec. 2023.
  • G. Joseph, C. Zhong, M. C. Gursoy, S. Velipasalar, and P. K. Varshney, “Scalable and Decentralized Algorithms for Anomaly Detection via Learning-Based Controlled Sensing,” IEEE Transactions on Signal and Information Processing over Networks, vol. 9, pp. 640-654, 2023.
  • X. Wang and M. C. Gursoy, “Resilient Path Planning for UAVs in Data Collection Under Adversarial Attacks,” in IEEE Transactions on Information Forensics and Security, vol. 18, pp. 2766-2779, 2023.
  • M. Guo and M. C. Gursoy, “Joint Activity Detection and Channel Estimation for Intelligent-Reflecting-Surface-Assisted Wireless IoT Networks,” in IEEE Internet of Things Journal, vol. 10, no. 12, pp. 10207-10221, June, 2023.
  • Y. Zhu, X. Yuan, Y. Hu, T. Wang, M. C. Gursoy and A. Schmeink, “Low-Latency Hybrid NOMA-TDMA: QoS-Driven Design Framework,” in IEEE Transactions on Wireless Communications, vol. 22, no. 5, pp. 3006-3021, May 2023.
  • Y. Zhu, Y. Hu, X. Yuan, M. C. Gursoy, H. V. Poor and A. Schmeink, “Joint Convexity of Error Probability in Blocklength and Transmit Power in the Finite Blocklength Regime,” in IEEE Transactions on Wireless Communications, vol. 22, no. 4, pp. 2409-2423, April 2023.
  • Y. Shi, Y. E. Sagduyu, T. Erpek and M. C. Gursoy, “How to Attack and Defend NextG Radio Access Network Slicing with Reinforcement Learning,” IEEE Open Journal of Vehicular Technology, vol. 4, pp. 181-192, 2023.
  • D. Deng, X. Li, S. Dang, M. C. Gursoy and A. Nallanathan, “Covert Communications in Intelligent Reflecting Surface-Assisted Two-Way Relaying Networks,” IEEE Transactions on Vehicular Technology, vol. 71, no. 11, pp. 12380-12385, Nov. 2022
  • X. Wang, M. C. Gursoy, T. Erpek, and Y. E. Sagduyu, “Learning-Based UAV Path Planning for Data Collection with Integrated Collision Avoidance,” IEEE Internet of Things Journal, vol. 9, no. 17, pp. 16663-16676, Sep. 2022.
  • X. Wang and M. C. Gursoy, “Learning-Based UAV Trajectory Optimization with Collision Avoidance and Connectivity Constraints,” IEEE Transactions on Wireless Communications, vol. 21, no. 6, pp. 4350-4363, Jun. 2022.
  • Z. Lu, C. Zhong, and M. C. Gursoy, “Dynamic Channel Access and Power Control in Wireless Interference Networks via Multi-Agent Deep Reinforcement Learning,” IEEE Transactions on Vehicular Technology, vol. 71, no. 2, pp. 1588-1601, Feb. 2022.
  • Z. Xu, J. Tang, C. Yin, Y. Wang, G. Xue, J. Wang, M. C. Gursoy, “ReCARL: Resource Allocation in Cloud RANs with Deep Reinforcement Learning,” EEE Transactions on Mobile Computing, vol. 21, no. 7, pp. 2533-2545, Jul. 2022
  • M. Guo and M. C. Gursoy, “Joint Activity Detection and Channel Estimation in Cell-Free Massive MIMO Networks with Massive Connectivity,” IEEE Transactions on Communications, vol. 70, no. 1, pp. 317-331, Jan. 2022.
  • H. Huang, D. Qiao and M. C. Gursoy, “Age-Energy Tradeoff Optimization for Packet Delivery in Fading Channels,” IEEE Transactions on Wireless Communications, vol. 21, no. 1, pp. 179-190, Jan. 2022.
  • F. Wang, C. Zhong, M. C. Gursoy, and S. Velipasalar, “Resilient Dynamic Channel Access via Robust Deep Reinforcement Learning,” IEEE Access, vol. 9, pp. 163188-163203, 2021.
  • P. Sinha, I. Guvenc, and M. C. Gursoy, “Fundamental Limits on Detection of UAVs by Existing Terrestrial RF Networks,” IEEE Open Journal of the Communications Society, vol. 2, pp. 2111-2130, 2021
  • X. Wang and M. C. Gursoy, “Uplink Coverage in Heterogeneous mmWave Cellular Networks with Clustered Users,” IEEE Access, vol. 9, 2021.
  • M. Guo and M. C. Gursoy, “Statistical Learning Based Joint Antenna Selection and User Scheduling for Single-Cell Massive MIMO Systems,” IEEE Transactions on Green Communications and Networking, vol. 5, no. 1, pp. 471-483, March 2021

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