Shuaihang Yuan

Postdoctoral Associate Affiliation: NYU Abu Dhabi
Education: BA StonyBrook University, Computer Science; MA New York University, Computer Science; PhD New York University, Computer Science

Research Websites: Center for Artificial Intelligence and Robotics (CAIR)

Research Areas: Computer vision, machine learning, multi-robot cooperation

Shuaihang Yuan received his BS degree in computer science from Stony Brook University (SBU), USA, in 2017. He received his MS degree in computer science from Tandon School of Engineering, New York University, USA, in 2019. He received his PhD at Tandon School of Engineering, New York University, USA. He is currently a Postdoctoral Associate with the Center for Artificial Intelligence and Robotics at New York University Abu Dhabi. His research interests include multi-modality computer vision and multi-robot cooperation.

Current Research

Shuaihang Yuan's research portfolio exhibits a profound engagement with several core areas of computer vision and robotics, particularly focusing on the perception of 3D environments. His work, on 3D segmentation has contributed to more accurate parsing of complex spatial scenes into distinct objects and surfaces. His methodologies facilitate machines in recognizing individual objects within a 3D space with only one-shot supervision. In the realm of 3D object detection, Yuan has developed algorithms that enable the identification and classification of objects in three-dimensional space with remarkable precision with only few-shot supervision. This research is crucial for autonomous systems, which require robust detection capabilities to navigate and interact with their environments safely. Yuan has now moved his focus to build a robust 3D semantic SLAM system, which is pivotal for robots and autonomous agents to build a map of an unknown environment while simultaneously tracking their location and understanding the semantic information within it. Overall, Yuan's research outputs advance the understanding and application of computer vision and robotics in 3D environments.