Ming-Fang Chang
Papers
6
Total Citations
1,707
H-Index
6
About
Ming-Fang Chang is a leading researcher in autonomous vehicle perception and assistive robotics, whose work bridges cutting-edge AI with real-world mobility challenges. Chang is best known as a core contributor to the Argoverse project, a landmark dataset for 3D tracking and motion forecasting that has garnered over 1,500 citations. This resource, collected from autonomous vehicle fleets in Pittsburgh and Miami, provides richly annotated sensor data that has become a standard benchmark for advancing self-driving car perception systems. Prior to this, Chang made significant contributions to healthcare robotics, developing context-aware robotic walkers for Parkinson’s disease patients and the elderly. Their work on the CAIROW (Context-aware Assisted Interactive Robotic Walker) system—the first active robotic walker designed specifically for Parkinson’s patients—integrates sensor fusion and human-robot interaction to prevent falls and improve quality of life. Chang’s research also includes multi-robot cooperation for human tracking using laser range finders, demonstrating expertise in both autonomous systems and human-centered robotics. With a career spanning foundational datasets and life-changing assistive devices, Chang exemplifies how rigorous engineering can drive both technological progress and social impact.
Research Focus
Key Achievements
Top Papers
- 1Argoverse: 3D Tracking and Forecasting With Rich Maps1,420 citations · 2019
- 2Argoverse: 3D Tracking and Forecasting with Rich Maps157 citations · 2019
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- 4Multi-robot cooperation based human tracking system using Laser Range Finder41 citations · 2011
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