Boshi An
Papers
2
Total Citations
7
H-Index
2
About
Boshi An is an emerging researcher in the field of robotics and machine learning, with a focus on scalable robot learning, manipulation policies, and generalizable robotic systems. Their work addresses some of the most pressing challenges in enabling robots to operate effectively in real-world environments, particularly in domestic and assistive settings. Among their most notable contributions is the development of **RoboVerse** (2025), a unified platform, benchmark, and dataset designed to advance scalable and generalizable robot learning — a timely and ambitious effort that has already garnered early attention with 5 citations shortly after publication. This work reflects a systems-level thinking that bridges simulation infrastructure with practical robot learning benchmarks. An has also contributed meaningfully to the problem of 3D articulated object manipulation through **ImageManip** (2023), which introduces an image-based approach with affordance-guided next view selection — offering a compelling alternative to point cloud-dependent methods that often struggle with real-world complexity. Though early in their career, Boshi An's research demonstrates a clear trajectory toward impactful contributions in embodied AI and robotic manipulation, areas that are central to the next generation of intelligent, autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2