Jielun Zhang

Jielun ZHANG

Ph.D. Student

Electrical & Computer Engineering

University of Dayton

Lab: KL 351F

E-mail: zhangj46@udayton.edu

Phone: (937) 660-6606

Education

• • PhD student, Electrical Engineering, University of Dayton, Expected May 2022

  • MS, Electrical Engineering, University of Dayton, Aug 2018

    • Thesis: Application-aware Traffic Prediction and User-aware Quality-of-Experience Measurement in Smart Network

    • - GPA 4.0

  • BS, Electronic and Computer Eng Technology, University of Dayton, May 2016

    • - GPA 3.95

  • BS, Electrical Engineering, Shanghai Normal University, Shanghai, China, July 2016

Working Experience

• • Graduate Research Assistant , University of Dayton, Dayton, OH Sept. 2017 – Present

  • Engineering Intern in R&D department, Branson Ultrasonic, Emerson Automation Solution, Danbury, CT May 2017 – Aug 2017

  • Academic Assistant , University of Dayton, Dayton, OH Sept. 2016 – May 2017

Publications

Journal Papers

1. Venkataramani Kumar, Jiahui Yu, Fuhao Li, Jielun Zhang, Feng Ye, Sanjeevi Karri, and Guru Subramanyam, "Seamless Wireless Communication Platform for Internet of Things Applications," IEEE Wireless Communications, 2022.

2. Jielun Zhang, Fuhao Li, and Feng Ye, “Sustaining the High Performance of AI-based Network Traffic Classification Models,” IEEE/ACM Transactions on Networking, 2022.

3. Jielun Zhang, Fuhao Li, and Feng Ye, “Network Traffic Clustering with QoS-Awareness,” in IEEE/CIC China Communications, vol. 19, no. 3, pp. 202-214, March 2022, doi: 10.23919/JCC.2022.03.015.

4. Jielun Zhang, Feng Ye and Yi Qian, “Intelligent and Application-aware Network Traffic Prediction in Smart Access Gateways,” in IEEE Network, vol. 34, no. 3, pp. 264-269, May/June 2020, doi: 10.1109/MNET.001.1900513.

Under submission

1. Jielun Zhang, Fuhao Li, and Feng Ye, “Towards Quality-Explainable Data Synthesis for AI-based Network Intrusion Detection System,” submitted to IEEE Transactions on Big Data, 2022.

Conference Papers

1. Khalil Alsulami, Jielun Zhang, and Feng Ye, “Improvement on a Traffic Data Generator for Networking AI Algorithm Development,” IEEE GLOBECOM 2021, Dec. 2021.

2. Venkataramani Kumar, Fuhao Li, Jielun Zhang, Feng Ye and Guru Subramanyam, “A Machine Learning Approach to Modulation Detection in Wireless Communications,” IEEE NAECON 2021, Sept. 2021.

3. Khalil Alsulami, Jielun Zhang, and Feng Ye, “A Real Application Enable Traffic Generator for Networking AI Model Development,” IEEE ICC 2021.

4. Jielun Zhang, Fuhao Li, and Feng Ye, “An Ensemble-based Network Intrusion Detection Scheme with Bayesian Deep Learning,” IEEE ICC 2020.

5. Jielun Zhang, Fuhao Li, Feng Ye, and Hongyu Wu, "Autonomous Unknown-Application Filtering and Labeling for DL-based Traffic Classifier Update," IEEE INFOCOM 2020.

6. Jielun Zhang, Fuhao Li, Hongyu Wu and Feng Ye, "Autonomous Model Update Scheme for Deep Learning based Network Traffic Classifiers," IEEE GLOBECOM 2019, Dec. 9-13, 2019, Waikoloa, HI.

7. J Yang, J Zhang, F Ye, X Cheng, "A UAV Based Multi-object Detection Scheme to Enhance Road Condition Monitoring and Control for Future Smart Transportation." International Conference on Artificial Intelligence for Communications and Networks. Springer, Cham, 2019.

8. Zhang, J., Ye, F. and Qian, Y., “A Distributed Network QoE Measurement Framework for Smart Networks in Smart Cities,” 2018 IEEE International Smart Cities Conference (ISC2).

Presentations

• • “A Distributed Network QoE Measurement Framework for Smart Networks in Smart Cities,” 2018 IEEE International Smart Cities Conference, Sept. 17, 2018.

Reviewer

• • IEEE Transactions on Vehicular Technology

  • IEEE Internet of Things Journal

  • IEEE/CIC China Communications

Professional Affiliations

• • IEEE Student Member

    • IEEE ComSoc Student Member

    • IEEE VTS Student Member

Honors and Awards

• • Graduate Student Summer Fellowship 2021

    • Sustaining the Intelligence of AI-based Network Traffic Classifiers

  • Graduate Student Summer Fellowship 2019

    • A Learning-based Framework for Packet Classification and Network Traffic Flow Clustering in SDN Access Gateways

  • Graduate Student Summer Fellowship 2018

    • Proposal titled in Establish Reliable and Energy Efficient Public Safety Communication Networks using Future Smart Infrastructure.

  • Graduated Summa Cum Laude 2016

Computer Skills

PyTorch, MATLAB , LabVIEW, LaTeX, MS Excel, MS Visio