Shuaiqi (Roger) Shen

Dr. Shuaiqi Shen joined the Department of Electrical Engineering at the University of Wisconsin-Milwaukee (UWM) in August 2022. Dr. Shen’s research interests cover broad areas of embedded systems, including edge intelligence, energy-efficient communication, network security and the Internet-of-Things.

Dr. Shen welcomes undergraduate, masters and doctoral students to join his research group. For an application and more information, please contact him at shen8@uwm.edu.

Education

• PhD, Electrical and Computer Engineering, University of Nebraska-Lincoln, 2022
• M Phil, System Engineering and Engineering Management, Chinese University of Hong Kong, 2018
• BS, Electronics and Information Engineering, Polytechnic University of Hong Kong, 2016

Research Interests

• Embedded systems
• AI-empowered Internet-of-Things
• Edge-assisted collaborative learning
• Energy-efficient communication

Selected Publications

Google Scholar link

• Shen, B. Liu, K. Zhang, and S. Ci, “Toward Fast and Accurate SOH Prediction for Lithium-ion Batteries”, IEEE Transactions on Energy Conversion, vol. 36, no. 3, pp. 2036-2046, 2021.
• Shen, C. Yu, K. Zhang, J. Ni, and S. Ci, “Adaptive Artificial Intelligence for Resource-constrained Connected Vehicles in Cybertwin-driven 6G Network”, IEEE Internet of Things Journal, vol. 8, no. 22, pp. 16269-16278, 2021.
• Shen, C. Yu, K. Zhang, J. Ni, and S. Ci, “Adaptive and Dynamic Security in 6G: From an Energy Efficiency Perspective”, IEEE Communications Standards Magazine, vol. 5, no. 3, pp. 80-88, 2021.
• Shen, K. Zhang, Y. Zhou, and S. Ci, “Security in edge-assisted Internet of Things: challenges and solutions”, Science China Information Sciences, vol. 63, no. 12, pp. 1-14, 2020.
• Yu, S. Shen, H. Yang, K. Zhang, and H. Zhao, “Leveraging Energy, Latency and Robustness for Routing Path Selection in Internet of Battlefield Things”, IEEE Internet of Things Journal, vol. 9, no. 14, pp. 12601 - 12613, 2022.
• Li, X. Chen, S. Shen, R. Zhang, and E. MacPherson, “Genetic-Algorithm-Based Optimization for Terahertz Time-Domain Adaptive Sampling”, IEEE Transactions on Terahertz Science and Technology, vol. 9, no. 6, pp. 675-683, 2019.
• Shen, C. Yu, K. Zhang, and S. Ci, “Collaborative Edge Caching with Personalized Modeling of Content Popularity over Indoor Mobile Social Networks”, Proc. of IEEE of ICC'22, Seoul, Korea, May 16-20, 2022.
• Yu, S. Shen, S. Wang, K. Zhang, and H. Zhao, “Efficient Multi-Layer Stochastic Gradient Descent Algorithm for Federated Learning in E-health”, Proc. of IEEE of ICC'22, Seoul, Korea, May 16-20, 2022.
• Yu, S. Shen, K. Zhang, H. Zhao, and Y. Shi, “Energy-Aware Device Scheduling for Joint Federated Learning in Edge-assisted Internet of Agriculture Things”, Proc. of IEEE WCNC'22, Austin, TX, April 10-13, 2022.
• Shen, C. Yu, K. Zhang, and S. Ci, “Exploiting Feature Interactions for Malicious Website Detection with Overhead-accuracy Tradeoff”, Proc. of IEEE ICC'21, Montreal, QC, Canada, June 2021.
• Shen, C. Yu, K. Zhang, X. Chen, H. Chen, and S. Ci, “Communication-Efficient Federated Learning for Connected Vehicles with Constrained Resources”, Proc. of IEEE IWCMC, Harbin, China, June 28-July 2, 2021.
• Shen, K. Zhang, S. Ci, and X. Liang, “Lifecycle Prediction of Second Use Electric Vehicle Batteries Based on ARIMA Model”, IEEE Globecom Workshop on Cyber-Physical Energy System for Sustainable ICT (CYPESS), Waikoloa, HI, USA, December 9-13, 2019.