Scholar
Ruxiao Chen
Google Scholar ID: uVfCFjwAAAAJ
Johns Hopkins University, PhD student
Citations & Impact
Citations
26
H-index
2
i10-index
2
Publications
5
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- - 'Look-Ahead Task Offloading for Multi-User Mobile Augmented Reality in Edge-Cloud Computing', published in IEEE Network Magazine
- - 'From Perceptions to Decisions: Wildfire Evacuation Decision Prediction with Behavioral Theory-informed LLMs', accepted by ACL 2025 Main Conference
- - 'Referential Task-Oriented Emergent Semantic Communications for Mobile Augmented Reality', published in 2024 IEEE/CIC International Conference on Communications in China (ICCC Workshops)
- - 'Agent in the Sky: Intelligent Multi-Agent Framework for Autonomous HAPS Coordination and Real-World Event Adaptation', published in AAAI 2025 Workshop on Artificial Intelligence for Wireless Communications and Networking (AI4WCN)
- - 'Few-Shot Adaptive Learning for Robust Task-Oriented Semantic Communication', published in AAAI 2025 Workshop on Artificial Intelligence for Wireless Communications and Networking (AI4WCN)
Research Experience
- - Research Assistant at Johns Hopkins University (2024.09 - present), working with Prof. Susu Xu
- - Visiting student at King Abdullah University of Science and Technology (KAUST), Saudi Arabia (2023.09 - 2023.12), working with Prof. Charalambos Konstantinou
- - Visiting student at South University of Science and Technology of China (2024.04 - 2024.08), working with Prof. Seungwoo Je
Education
- - Shandong University, Bachelor in Automation (2020-2024)
- - Johns Hopkins University, Master in Systems Engineering (2024-2025)
- - Johns Hopkins University, PhD in Systems Engineering (2025-present)
Background
- - PhD student in Systems Engineering at Johns Hopkins University, starting in Fall 2025
- - Supervisor: Prof. Susu Xu
- - Long-term goal: To build intelligent systems that reason about human behavior in complex social environments
- - Research Interests: Integrating large language models with psychological theories, designing multi-agent LLM frameworks
Co-authors