About

I’m a last-year Ph.D. student @ the University of Arizona. I’m working for the WiCON Lab in the department of electrical and computer engineering under supervision of Prof. Marwan Krunz. My primary research interests include adversarial machine learning for wireless networks, spectrum sharing, and mobile cloud/edge computing.

You can reach me by wenhanzhang@email.arizona.edu. Please feel free to contact me for any discussion or collaboration. I’m open to internships and full-time jobs.

News

• [04/2024] I will serve as a reviewer for IEEE Transactions on Communications.
• [03/2024] I have defended my final dissertation. [news]
• [02/2024] Our paper is accepted by IEEE Transactions on Machine Learning in Communications and Networking.
• [11/2023] Two papers are accepted by IEEE ICNC’24.
• [11/2023] Our paper is accepted by IEEE Transactions on Vehicular Technology.
• [03/2023] I will serve as a reviewer for Elsevier Computer Communications.
• [02/2023] I will serve as a reviewer for IEEE Transactions on Communications.
• [11/2022] One paper is accepted by IEEE ICNC’23.
• [11/2022] I will serve as a reviewer for IEEE Journal on Selected Areas in Communications.
• [10/2022] I will serve as a reviewer for Elsevier Computer Communications.
• [05/2022] I will join Intel Labs for the summer internship.
• [04/2022] I receive the NSF Student Travel Grant for IEEE ICC’22.
• [03/2022] Our paper is accepted by SPIE Defense + Commercial’22.
• [03/2022] One paper is accepted by IEEE ICC’22 Workshop on Spectrum Sharing Technology for Next Generation Communications.
• [11/2021] I receive the Student Travel Grant from IEEE Comsoc to attend MILCOM’21.
• [10/2021] One paper is accepted by IEEE MILCOM’21.
• [06/2021] I will serve as a reviewer for IEEE Transactions on Mobile Computing.
• [05/2021] Our paper is accepted by IEEE Transactions on Vehicular Technology.
• [01/2021] Two papers are accepted by IEEE INFOCOM’21 and workshops.
• [08/2020] One paper is accepted by IEEE GLOBECOM’20.

Publications

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

• CyPA: A cyclic prefix assisted DNN for protocol classification in shared spectrum, *Wenhan Zhang, Marwan Krunz, and Md Rabiul Hossein, Proc. of the IEEE International Conference on Computing, Networking and Communications (ICNC) 2024: AI and Machine Learning for Communications and Networking, Feb. 2024 (acceptance rate 24.10%). [paper]

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

• Latency estimation and computational task offloading in vehicular mobile edge computing applications, *Wenhan Zhang, Mingjie Feng, and Marwan Krunz, IEEE Transactions on Vehicular Technology (TVT), Nov. 2023, doi: 10.1109/TVT.2023.3334192. [paper]

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

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

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

• Joint task partitioning and user association for latency minimization in mobile edge computing networks, Mingjie Feng, Marwan Krunz, and *Wenhan Zhang, IEEE Transactions on Vehicular Technology (TVT), vol. 70, no. 8, pp. 8108-8121, Aug. 2021.

• Intelligent jamming of deep neural network based signal classification for shared spectrum, *Wenhan Zhang, Marwan Krunz, and Gregory Ditzler, Proc. of the IEEE Military Communications Conference (MILCOM) 2021 – Track 5, San Diego, Nov. 29 – Dec. 2, 2021. [paper]

• Task partitioning and user association for latency minimization in mobile edge computing networks, Mingjie Feng, Marwan Krunz, and *Wenhan Zhang, Proc. of the IEEE International Workshop on Intelligent Cloud Computing and Networking (ICCN) 2021 in conjunction with the IEEE INFOCOM 2021 Conference, May 2021.[paper]

• Signal detection and classification in shared spectrum: A deep learning approach, *Wenhan Zhang, Mingjie Feng, Marwan Krunz, Proc. of the IEEE International Conference on Computer Communications (INFOCOM) 2021 Conference, May 2021 (acceptance rate 19.9%). [paper]

• Latency prediction for delay-sensitive V2X applications in mobile cloud/edge computing systems, *Wenhan Zhang, Mingjie Feng, Marwan Krunz, and Haris Volos, Proc. of the IEEE Global Communications Conference (GLOBECOM) Conference, Taipei, Taiwan, Dec. 2020. [paper]