Resume
Academic Achievements
- Sep. 2025: Two co-authored papers accepted by NeurIPS 2025 (one spotlight)
- Aug. 2025: Paper titled 'Task-Aware Parameter-Efficient Fine-Tuning of Large Pre-Trained Models at the Edge' accepted by IEEE GLOBECOM 2025
- Apr. 2025: Paper titled 'R-ACP: Real-Time Adaptive Collaborative Perception Leveraging Robust Task-Oriented Communications' accepted by IEEE JSAC
- Aug. 2025: Awarded Outstanding Academic Performance Award (OAPA) Scholarship by City University of Hong Kong
- Mar. 2025: Received IEEE Robotics and Automation Society (RAS) Student Grant
- Sep. 2025: Passed PhD Qualifying Examination (QE)
Research Experience
- Conducts research at the Wireless Intelligence and Networked Things Laboratory (WINET) and JC STEM Lab of Smart City
- Works on efficient system design for connected autonomous driving, including task partitioning and communication scheduling
- Investigates real-world data fabrication attacks (e.g., cross-view and adaptive perturbations) and develops defense mechanisms for BEV and multi-stage pipelines
- Performs street view synthesis and data augmentation to generate rare and long-tail scenarios for improved model generalization
- Builds temporally consistent, interactive world models with 3D trajectory prediction for testing and real-time decision support
Background
- Research interests include collaborative perception, autonomous driving, and AI security
- Dedicated to designing robust and efficient systems for next-generation connected autonomous driving
- Focuses on system efficiency and security in multi-agent connected autonomous driving
- Leverages generative models for data augmentation and interactive world models to enhance generalization and decision-making
- Serves as a program committee member for ICML, ICLR, ACM MM, and reviewer for IEEE TITS, TMC, RA-L, etc.