Duy Lê

OverviewAI-generated summary

Duy Lê's research focuses on the application of machine learning techniques, particularly deep learning and neural networks, to complex data analysis problems. His work includes developing efficient attentive pillar networks for real-time 3D pedestrian detection and exploring diffusion models for multi-sensor fusion in 3D object detection and BEV segmentation. Lê has also investigated the use of deep convolutional neural networks for medical imaging, specifically for detecting atypical femur fractures from anterior-posterior radiographs. His research extends to dataset creation for multi-person pose estimation and tracking, as well as benchmarking approaches for long context in large language models. Lê's scholarly contributions are reflected in his h-index of 6 and 20 total publications.

Metrics

• h-index: 6
• Publications: 20
• Citations: 139