Adam Srebrnjak Yang

University of Waterloo

Papers

1

Total Citations

3

H-Index

1

About

Adam Srebrnjak Yang is a rising researcher at the forefront of real-time 3D vision and robotics, specializing in simultaneous localization and mapping (SLAM) and dense 3D reconstruction. His work addresses the critical challenge of enabling resource-constrained devices—such as drones and mobile robots—to perceive and map their environments in real time. Yang’s most notable contribution is the development of MGSO (Monocular Gaussian Splatting SLAM), a pioneering system that integrates photometric SLAM with efficient 3D Gaussian Splatting (3DGS). This approach achieves unprecedented real-time dense 3D mapping on a single CPU, overcoming the computational bottlenecks that have long plagued SLAM systems. By leveraging 3DGS, Yang’s method delivers high-fidelity reconstructions without the need for expensive GPUs, making it ideal for edge computing. Although his work is recent, with MGSO already garnering 3 citations, it represents a significant leap forward in democratizing advanced SLAM capabilities. Yang’s research promises to unlock new possibilities in autonomous navigation, augmented reality, and field robotics, establishing him as a key innovator in efficient 3D perception.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
MGSO: Monocular Real-Time Photometric SLAM with Efficient 3D Gaussian Splatting
3 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: University of Waterloo

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago