Journals

• Sopan Sarkar, Phai Vu Dinh, Marwan Krunz, Santosh Timilsina, Diep N. Nguyen, and Sangkyo Shin, "AI-based spatio-temporal beam prediction from partial CSI-RS observations in mmWave systems," accepted for the IEEE Transactions on Machine Learning in Communications and Networking (TMLCN), Sept. 2026.

• Phai Vu Dinh, Diep N. Nguyen, Dinh Thai Hoang, Marwan Krunz, Quang Uy Nguyen, Son PhamBao, and Eryk Dutkiewicz, "Teacher-free latent self-distillation and class-separable representations for lightweight IoT attack detection," accepted for the IEEE Internet of Things Journal, Sept. 2026.

• Arush S. Sharma and Marwan Krunz, "Weakly supervised machine learning for enhanced RFI detection in astronomical observations," accepted for the Astronomy and Astrophysics (A&A), Aug. 2026.

• Ahsan Aqueeb, Hamid Ravaee, Mohammad Hossein Manshaei, Marwan Krunz, Jiacheng Ding, Julia Morris, Darren A. Cusanovich, and Curtis Thorne, "SynCellNet: Generative AI framework for single-cell RNA sequencing data generation and validation," accepted for the Scientific Reports, July 2026.

• Yong Xiao, Xubo Li, Haoran Zhou, Yingyu Li, Yayu Gao, Guangming Shi, Ping Zhang, and Marwan Krunz, "SANet: A semantic-aware agentic AI networking framework for cross-layer optimization in 6G," IEEE Transactions on Mobile Computing (TMC), vol. 25, pp. 14849-14866, May 2026, doi: 10.1109/TMC.2026.3691804.

• Sopan Sarkar, Marwan Krunz, David Manzi, and Rajesh Kulkarni, "ARCS: Adversarial RF map categorization and synthesis through unsupervised feature extraction," IEEE Transactions on Machine Learning in Communications and Networking (TMLCN), vol. 4, pp. 612-628, Mar. 2026, doi: 10.1109/TMLCN.2026.3676377.

• Bui Minh Tuan, Van-Dinh Nguyen, Diep N. Nguyen, Nguyen Linh Trung, Nguyen Van Huynh, Dinh Thai Hoang, Marwan Krunz, and Eryk Dutkiewicz, "Deep learning-driven friendly jamming for secure multicarrier ISAC under channel uncertainty," IEEE Transactions on Communications, vol. 74, pp. 6332-6348, Mar. 2026, doi: 10.1109/TCOMM.2026.3675471.

• Sopan Sarkar, Marwan Krunz, Sherif Badran, Josep M Jornet, David Manzi, and Rajesh Kulkarni, "GAMBIT: A generalized adaptive multi-armed bandit for intelligent beam tracking and rate adaptation," IEEE Transactions on Vehicular Technology, vol. 74, pp. 17683-17696, Nov. 2025, doi: 10.1109/TVT.2025.3580601.

• Bui Minh Tuan, Van-Dinh Nguyen, Nguyen Van Huynh, Diep N. Nguyen, Dinh Thai Hoang, Marwan Krunz, Nguyen Linh Trung, and Eryk Dutkiewicz, "Securing MIMO wiretap channel with learning-based friendly jamming under imperfect CSI," IEEE Internet of Things Journal, vol. 12, pp. 16009-16022, June 2025, doi: 10.1109/JIOT.2025.3536702.

• Huixiang Zhu, Yong Xiao, Yingyu Li, Guangming Shi, and Marwan Krunz, “SANSee: A physical- layer semantic-aware networking framework for distributed wireless sensing,” IEEE Transactions on Mobile Computing (TMC), vol. 24, pp. 1636-1653, Mar. 2025, doi: 10.1109/TMC.2024.3483272.

• Zhiwu Guo, Chicheng Zhang, Ming Li, and Marwan Krunz, “Fair Probabilistic Multi-Armed Bandit with Applications to Network Optimization,” IEEE Transactions on Machine Learning in Communications and Networking (TMLCN), vol. 2, pp. 994-1016, June 2024, doi: 10.1109/TMLCN.2024.3421170.

• Amir Hossein Yazdani Abyaneh, Marwan Krunz, and Mohammed Hirzallah, “Countermeasuring aggressors via intelligent adaptation of contention window in CSMA/CA systems,” IEEE Access, vol. 12, pp. 88216-88230, June 2024, doi: 10.1109/ACCESS.2024.3416232.

• Wenhan Zhang, Marwan Krunz, and Greg Ditzler, "Stealthy adversarial attacks on machine learning-based classifiers of wireless signals," IEEE Transactions on Machine Learning in Communications and Networking (TMLCN), vol. 2, pp. 261-279, Feb. 2024, doi: 10.1109/TMLCN.2024.3366161.

• Marwan Krunz, Irmak Aykin, Sopan Sarkar, and Berk Akgun, “Online reinforcement learning for beam tracking and rate adaptation in millimeter-wave systems,” IEEE Transactions on Mobile Computing (TMC), vol. 23, issue 2, pp. 1830-1845, Feb. 2024.

• Yong Xiao, Xiaohan Zhang, Yingyu Li, Guangming Shi, Marwan Krunz, Diep Nguyen, and Dinh Thai Hoang, “Time-sensitive learning for heterogeneous federated edge intelligence,” IEEE Transactions on Mobile Computing (TMC), vol. 23, issue 2, pp. 1382-1400, Feb. 2024.

• Yong Xiao, Rong Xia, Yingyu Li, Guangming Shi, Diep N. Nguyen, Dinh Thai Hoang, Dusit Niyato, and Marwan Krunz, “Distributed traffic synthesis and classification in edge networks: Federated self- supervised learning approach,” IEEE Transactions on Mobile Computing (TMC), vol. 23, issue 2, pp. 1815-1829, Feb. 2024.

• M. Moghadam, B. Boroomand, M. Jalali, A. Zareian, A. Daeijavad, M. Hossein Manshaei, and M. Krunz, “Games of GANs: Game-theoretical models for generative adversarial networks,” Artificial Intelligence Review, vol. 56, no. 9, pp. 9771--9807, Jan. 2023.

• Peyman Siyari, Hanif Rahbari, and Marwan Krunz, “Lightweight machine learning for efficient frequency-offset-aware demodulation,” IEEE Journal on Selected Areas in Communications (JSAC) - Special Issue on Machine Learning in Wireless Communications, vol. 37, no. 11, pp. 2544-2558, Nov. 2019.

Conferences

• Sopan Sarkar and Marwan Krunz, "Physics-Informed Kernelized Thompson Sampling for Beam Management in Millimeter-Wave Systems," accepted for the ACM MobiHoc'26 Conference, Tokyo, 2026.

• Phai Vu Dinh, Diep N. Nguyen, Hoang Thai Dinh, Marwan Krunz, Nguyen Quang Uy, Son Pham Bao, and Eryk Dutkiewicz, "Teacher-Free Latent Self-Distillation for Lightweight IoT Intrusion Detection," accepted for the IEEE Globecom'26 Conference, 2026.

• Yong Xiao, Haoran Zhou, Yujie Zhou, and Marwan Krunz, "SANEmerg: An emergent communication framework for semantic-aware agentic AI networking," Proc. of the IEEE/IFIP International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt’26) – Workshop on Modeling and Optimization for Semantic Communications (MOSC) Conference, Columbus, Ohio, June 2026.

• Sopan Sarkar and Marwan Krunz, "SAIL: Unsupervised spatial-angular interpretable feature learning for RF map synthesis," Proc. of the IEEE ICCSPA'26 Conference, June 2026.

• Md Rabiul Hossain, Ayushi Dube, Arush S. Sharma, Gian Singh, Marwan Krunz, and Sarma Vrudhula, "Energy-efficient low-latency protocol and modulation classification for edge devices," Proc. of the IEEE ICCSPA'26 Conference, June 2026.

• Bui Minh Tuan, Van-Dinh Nguyen, Diep N. Nguyen, Nguyen Linh Trung, Nguyen Van Huynh, Hoang Thai Dinh, Marwan Krunz, and Eryk Dutkiewicz, "Deep learning-driven friendly jamming for secure ISAC under channel uncertainty," Proc. of the IEEE ICC 2026 Conference - Wireless Communications Symposium, May 2026.

• Phai Vu Dinh, Marwan Krunz, Diep Nguyen, and Hoang Thai Dinh, "PFAE: Personalized federated learning for anomaly detection over heterogeneous IoT domains," Proc. of the IEEE INFOCOM Conference, May 2026.

• Arush S. Sharma and Marwan Krunz, "Transformer-based DNN for identification of RFI sources in astronomical observations," Proc. of the IEEE ICNC Conference, Hawaii, Feb. 2026.

• Bui Minh Tuan, Diep N. Nguyen, Nguyen Linh Trung, Van-Dinh Nguyen, Nguyen Van Huynh, Dinh Thai Hoang, Marwan Krunz, and Eryk Dutkiewicz, "Securing MIMO wiretap channel with DDPG-based friendly jamming under non-differentiable channel," Proc. of the IEEE ICC Conference - Workshop on Machine Learning and Deep Learning for Wireless Security, Montreal, Canada, June 2025.

• Zhiwu Guo, Chicheng Zhang, Ming Li, and Marwan Krunz, “Efficient fair probabilistic multi-armed bandit for real-time resource allocation in spectrum sharing,” Proc. of the IEEE DySPAN Conference, London, May 2025.

• Md Rabiul Hossain and Marwan Krunz, “PCI classification in 5G NR: Deep learning unravels synchronization signal blocks,” Proc. of the IEEE SECON Conference, Dec. 2024.

• Wenhan Zhang, Meiyu Zhong, Ravi Tandon, and Marwan Krunz, "Filtered randomized smoothing: A new defense for robust modulation classification," Proc. of the IEEE MILCOM Conference, Oct. 2024.

• Sopan Sarkar, Mohammad Hossein Manshaei, Marwan Krunz, and Hamid Ravaee, “RecuGAN: A novel generative AI approach for synthesizing RF coverage maps,” Proc. of the IEEE International Conference on Computer Communications and Networks (ICCCN) Conference, July 29–31, 2024, Kona (Big Island), Hawaii.

• Arush S. Sharma and Marwan Krunz, "Enhanced RFI detection in imbalanced astronomical observations using weakly supervised GANs,” Proc. of the IEEE ICC Conference - Workshop on Catalyzing Spectrum Sharing via Active-Passive Coexistence, Denver, June 2024.

• Wenhan Zhang, Marwan Krunz, and Md Rabiul Hossain, “CyPA: A cyclic prefix assisted DNN for protocol classification in shared spectrum,” Proc. of the International Conference on Computing, Networking and Communications (ICNC) - AI and Machine Learning for Communications and Networking Symposium, Feb. 2024.

• Zhiwu Guo, Wenhan Zhang, Ming Li, Marwan Krunz, and Mohammad Hossein Manshaei, "DL-SIC: Deep learning aided successive interference cancellation in shared spectrum,” Proc. of the International Conference on Computing, Networking and Communications (ICNC) - AI and Machine Learning for Communications and Networking Symposium, Feb. 2024.

• Arush Sharma, Marwan Krunz, George Reiland, and Dan Marrone, “Identification of RF interference in astronomical observations using weakly supervised machine learning classifiers,” Proc. of the ACM International Conference on Modeling, Analysis, and Simulation of Wireless and Mobile Systems (MSWiM), Montreal, Canada, Oct. 2023.

• Zhengguang Zhang and Marwan Krunz, "Detection and classification of smart jamming in Wi-Fi networks using machine learning," Proc. of the IEEE MILCOM Conference (TRACK 5 – Machine Learning for Communications and Networking), Oct. 2023.

• Sopan Sarkar, Hossein Manshaei, and Marwan Krunz, “RADIANCE: Radio-frequency adversarial deep-learning inference for automated network coverage estimation,” Proc. of the IEEE GLOBECOM Conference, 2023.

• Zhiwu Guo, Chicheng Zhang, Ming Li, and Marwan Krunz, “Fair coexistence of heterogeneous networks: A novel probabilistic multi-armed bandit approach,” Proc. of the International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) Conference, Singapore, Aug. 2023.

• Mingjie Feng, Wenhan Zhang, and Marwan Krunz, "Dynamic spectrum access in non-stationary environments: A DRL-LSTM integrated approach", Proc. of the International Conference on Computing, Networking and Communications (ICNC): AI and Machine Learning for Communications and Networking, pp. 159-164, Feb. 2023.

• Amir-Hossein Yazdani-Abyaneh and Marwan Krunz, “Automatic machine learning for multi-receiver CNN technology classifiers,” Proc. of the ACM Workshop on Wireless Security and Machine Learning (WiseML), San Antonio, Texas, May 2022.

• Wenhan Zhang and Marwan Krunz, "Machine learning based protocol classification in unlicensed 5 GHz bands," Proc. of the IEEE ICC 2022 Conference - Workshop on Spectrum Sharing Technology for Next Generation Communications, Seoul, South Korea,  May, 2022.

• Marwan Krunz and Wenhan Zhang, “Application of adversarial machine learning in protocol and modulation misclassification,” Proc. of the Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications Conference (part of SPIE Defense and Commercial Sensing Symposium), Orlando, FL, April 2022.

• Steve Chan, Marwan Krunz, and Bob Griffin, “Adaptive time-frequency synthesis for waveform discernment in wireless communications,” Proc. of the IEEE Information Technology, Electronics and Mobile Communication Conference (IEEE IEMCON), Oct. 2021.

• Wenhan Zhang, Marwan Krunz, and Gregory Ditzler, “Intelligent jamming of deep neural network based signal classification for shared spectrum,” Proc. of the IEEE MILCOM Conference – Track 5, San Diego, Nov. 29 – Dec. 2, 2021.

• Sopan Sarkar, Marwan Krunz, Irmak Aykin, and David Manzi, “Machine learning for robust beam tracking in mobile millimeter-wave systems,” Proc. of the IEEE GLOBECOM Conference, Madrid, Spain, Dec. 2021.

• Amir Yazdani Abyaneh and Marwan Krunz, “CWmin estimation and collision identification in Wi-Fi systems,” Proc. of the IEEE International Conference on Mobile Ad Hoc and Smart Systems (MASS), Oct. 2021 (invited paper).

• Steve Chan, Marwan Krunz, Bob Griffin, "AI-based robust convex relaxations for supporting diverse QoS in next-generation wireless systems," Proc. of the IEEE ICDCS Workshop - Next-Generation Mobile Networking and Computing (NGMobile 2021), July 2021.

• Mohammed Hirzallah and Marwan Krunz, “Sense-Bandits: AI-based adaptation of sensing thresholds for heterogeneous-technology coexistence over unlicensed bands,” Proc. of the International Conference on Computer Communications and Networks (ICCCN 2021), July 2021 (invited paper).

• Mingjie Feng and Marwan Krunz, “Program placement optimization for storage-constrained mobile edge computing systems: A multi-armed bandit approach,” Proc. of the 22nd IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM ’21), June 2021.

• Wenhan Zhang, Mingjie Feng, Marwan Krunz, and Amir Abyaneh, “Signal detection and classification in shared spectrum: A deep learning approach,” Proc. of the IEEE INFOCOM 2021 Conference, May 2021 (acceptance rate 19.9%). 

• Wenhan Zhang, Mingjie Feng, Marwan Krunz, and Haris Volos, “Latency prediction for delay-sensitive V2X applications in mobile cloud/edge computing systems,”  Proc. of the IEEE GLOBECOM Conference, Taipei, Taiwan, December 2020.

• Rong Xia, Yong Xiao, Yingyu Li, Marwan Krunz, and Dusit Niyato, “A generative learning approach for spatio-temporal modeling in connected vehicular setworks,”  Proc. of the IEEE ICC Conference - Wireless Communications Symposium, Dublin, Ireland, June 2020.

• Irmak Aykin, Berk Akgun, Mingjie Feng, and Marwan Krunz, “MAMBA: A multi-armed bandit framework for beam tracking in millimeter-wave systems,” Proc. of the IEEE INFOCOM 2020, Online, July 2020, pp. 1469-1478 (acceptance rate 19.8%). [Presentation] 

• Alex Berian, Irmak Aykin, Marwan Krunz, and Tamal Bose, “Deep learning based identification of wireless protocols in the PHY layer,” Proc. of the IEEE CNC Workshop, Big Island, Hawaii, Feb. 2020, pp. 287-293.

• Mohammed Hirzallah and Marwan Krunz, “Intelligent tracking of network dynamics for cross-technology coexistence over unlicensed bands,” Proc. of the IEEE ICNC 2020, Big Island, Hawaii, Feb. 2020, pp. 698-703.

• Amirhossein Yazdani Abyaneh, Mohammed Hirzallah, and Marwan Krunz, “Intelligent-CW: AI-based framework for controlling contention window in WLANs,” Proc. of the IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN’19), Newark, Nov 2019.

• Hanif Rahbari, Peyman Siyari, Marwan Krunz, and Jerry Park, “Adaptive demodulation for wireless systems in the presence of frequency-offset estimation errors,” Proc. of the IEEE INFOCOM 2018 Conference, Honolulu, HI, 2018, pp. 1592-1600 (acceptance rate 19.2%).