About

Yingli Tian is a multidisciplinary researcher whose work spans computer vision, robotics, assistive technology, and autonomous systems. With a career bridging foundational vision research — dating back to early work on surface shape and reflectance estimation in 1995 — to cutting-edge developments in wearable robotics and 3D scene understanding, Tian has established herself as a versatile and impactful figure in her field. Her most cited contribution (88 citations) is a pioneering hybrid soft exoskeleton designed for knee injury prevention, addressing critical challenges in human movement restriction and adaptive control of wearable co-robotic systems. Tian has also made significant strides in 3D point cloud processing, with her FESTA framework for scene flow estimation accumulating 43 citations and her survey on sequential point clouds reflecting her role as a synthesizer of emerging research directions. Her work in assistive navigation — including a SLAM-based indoor system for visually impaired users (37 citations) and indoor signage detection to aid the blind — demonstrates a sustained commitment to socially impactful technology. Complementing these contributions, her research on self-supervised monocular depth learning further underscores her expertise in robust perception for autonomous and assistive robots. Across these domains, Tian's work consistently bridges theoretical innovation with real-world human-centered applications.

Research Focus

Key Achievements

6
H-Index
11
Papers
223
Total Citations
20
Avg Citations/Paper
🏆 Most Cited Paper
Design and Control of a High-Torque and Highly Backdrivable Hybrid Soft Exoskeleton for Knee Injury Prevention During Squatting
88 citations · 2019
📈 Most Prolific Year: 2021 (3 Papers)
🤝 Key Collaborators: 33
🏛 Institutions: City University of New York, City College of New York, The Graduate Center, CUNY, Chinese University of Hong Kong

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago