PhD Researcher
Shiwei Shen has a Master of Science degree in Electrical Engineering, Information Technology, and Computer Engineering, with a concentration on communication networks. He completed his bachelor’s and master’s degrees at RWTH Aachen University, Germany, earning recognition including the RWTH Dean’s List Award and the FFV Master Thesis Award. His practical expertise was enhanced during an internship at Ericsson Eurolab, where he concentrated on Vehicle-to-Everything (V2X) relaying. In addition to his studies, he also has experience in full-stack web development.
He is currently a Ph.D. student at TU Dresden’s Deutsche Telekom Chair of Communication Networks. His present work revolves around the DymoBat project, which goal is to develop marketable solutions for future energy grid management for the use of distributed energy resources based on the application of 5G technologies. His research interest includes Vehicle-to-Grid (V2G), Internet of Energy (IoE), Optimization, and Spectrum Sharing. Complementing his research, he served as a reviewer for conferences and journals, such as European Wireless, IEEE TNSM, and IEEE Access.
Office: Building BAR S16
Email: shiwei.shen@tu-dresden.de
Phone: 0351 46340779
Current open topics: link
Data-Driven Insights: A Machine Learning Based EV Charging Behavior Prediction with Heterogeneous Users Proceedings Article
In: IEEE Global Power, Energy and Communication Conference (IEEE GPECOM 2025), pp. 6, Bochum, Germany, 2025.
Exploring V2G Flexibility in Dresden: A Temporal and Spatial Mapping Approach using SUMO Proceedings Article
In: Electric Vehicle Symposium & Exhibition (EVS), pp. 9, Gothenburg, Sweden, 2025.
Incentive-Driven V2B Energy Management via a Stackelberg Game Approach Proceedings Article
In: International Electric Vehicle Symposium & Exhibition (EVS), pp. 10, Gothenburg, Sweden, 2025.
Addressing EV Users' Bi-Directional Charging Anxiety in Workplaces: A Survey-Based Approach Proceedings Article
In: International Electric Vehicle Symposium & Exhibition (EVS), pp. 12, Gothenburg, Sweden, 2025.
Adaptive Scheduling of Bidirectional EV Using SAC-Based Reinforcement Learning for Enhanced Grid Flexibility Proceedings Article
In: International Electric Vehicle Symposium & Exhibition (EVS), pp. 12, Gothenburg, Sweden, 2025.
Simulation Architecture for Electric Vehicle Charging Optimization in Dresden's Ostra District Proceedings Article
In: pp. 1-10, Porto, Portugal, 2025.
Simulation Architecture for Electric Vehicle Charging Optimization in Dresden's Ostra District Proceedings Article
In: International Conference on Smart Cities and Green ICT Systems (SMARTGREENS), pp. 56–65, 2025, ISSN: 2184-4968.
Dynamic Optimization for Smart EV Charging: Insights from the DymoBat Project Proceedings Article
In: IEEE International Smart Cities Conference (ISC2), pp. 1-6, Pattaya, Thailand, 2024.
An Approach to Predict the Available Storage Capacity in Battery Electric Vehicle Fleets Proceedings Article
In: International Electric Vehicle Symposium & Exhibition (EVS), Seoul, Korea, 2024.
A Heuristic for Bi-Directional Charging of Fleet EVs Proceedings Article
In: IEEE Sustainable Power and Energy Conference (iSPEC), 2024.