Sandra Moffett
Papers
1
Total Citations
2
H-Index
1
About
Dr. Sandra Moffett is a leading researcher in artificial intelligence and autonomous systems, with a primary focus on pedestrian trajectory prediction for safe urban navigation. Her most-cited work introduces the GSTGM model—a groundbreaking framework that integrates graph neural networks, spatial-temporal attention mechanisms, and generative modeling to predict multiple plausible pedestrian paths in complex environments. This innovation addresses a critical challenge in autonomous vehicle and robotics safety, enabling systems to anticipate unpredictable human movements with unprecedented accuracy. While her 2024 paper has already garnered 2 citations, signaling growing recognition, Dr. Moffett’s broader contributions have shaped how researchers approach human-robot interaction in crowded spaces. Her work bridges the gap between theoretical AI advances and real-world deployment, directly impacting the development of safer autonomous navigation systems. By combining attention-based learning with generative modeling, she has provided a robust solution for multi-path prediction—a key bottleneck in urban autonomy. Dr. Moffett’s research continues to influence both academic inquiry and practical applications in smart cities and intelligent transportation.
Research Focus
Key Achievements
Top Papers
- 1