Scholar
Dongyue Huang
Google Scholar ID: wDFQQRsAAAAJ
The Chinese University of Hong Kong
Citations & Impact
Citations
139
H-index
5
i10-index
2
Publications
15
Co-authors
12
list available
Contact
No contact links provided.
Publications
Resume (English only)
Academic Achievements
- 1. Aug 22, 2025: Two papers related to Event-Camera have been accepted by ACM-MobiCom 2025.
- 2. Jul 3, 2025: Honored as a Shui Mu Tsinghua Scholar.
- 3. Jun 23, 2025: An IEEE-TIE paper has been transferred to be presented at IROS2025.
- 4. Jan 31, 2025: Our paper “Underwater Motions Analysis and Control of a Coupling-Tiltable Unmanned Aerial-Aquatic Vehicle” has been accepted by ICRA2025.
- 5. Nov 1, 2024: Our work “Aqua Slide: An Underwater Leveling Motion Scheme for M-UAAV Utilizing Singularity” has been accepted for publication by the IEEE Transactions on Industrial Electronics.
- 6. Jun 18, 2024: Our paper “First Principle Modeling of a Morphable Unmanned Aerial-Aquatic Vehicle: Mirs-Alioth” has been accepted by ICCA 2024.
- 7. Dec 25, 2023: Our work “Systematizing Rotor-Based Morphable Unmanned Aerial-Aquatic Vehicles Design: From Theory to Prototype” has been accepted by OCEANS 2024 Singapore.
- 8. Jul 27, 2023: Our group won the Guan Zhao-Zhi Award at the 42nd CCC2023.
- 9. Apr 23, 2023: Two papers have been accepted by CCC2023.
- 10. Jan 17, 2023: Two papers have been accepted by ICRA2023.
Research Experience
- Postdoctoral Fellow at Tsinghua University
Education
- Ph.D.: Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong (CUHK), Supervisor: Prof. Ben M. Chen
Background
- Research Interests: Developments of Morphable Aerial-Aquatic Vehicles, including their mechanical design, generalized design methodologies, dynamics analysis, controller design and implementation. Recently, my research focuses on intelligent aerial robots capable of physical interaction with the environment. In the short term, I am particularly interested in the design and control of morphable grasping UAVs, which can adapt their structure to perform complex manipulation tasks. In the long term, I aim to integrate aerial-aquatic robots with grasping capabilities, using reinforcement learning to ensure robustness in both flight and interaction across different mediums. Ultimately, my goal is to explore how LLMs can be incorporated into such systems to enable higher-level autonomy.
