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About

Djamila Aouada is a leading researcher at the intersection of computer vision, robotics, and space engineering. Her work focuses on developing robust perception systems for autonomous navigation, particularly under challenging and dynamic conditions. Aouada's major contributions include advancing LiDAR odometry through novel deep learning frameworks, such as her work on "Deep Evidential LiDAR Odometry using Partial Optimal Transport" (DELO), which addresses the critical challenges of non-uniform point sampling and uncertainty in real-time 3D mapping. She has also pioneered self-supervised learning methods for visual place recognition, enabling robots to generalize across drastic appearance changes—a key requirement for long-term autonomy. Beyond terrestrial robotics, Aouada has made significant strides in space operations. She established the "Zero-G Lab," a multi-purpose facility designed to emulate micro-gravity conditions for testing orbital rendezvous and docking maneuvers. This facility, detailed in her highly cited 2023 paper (28 citations), provides a crucial on-ground testbed for space missions. Her interdisciplinary approach, bridging computer vision with practical aerospace engineering, has earned her recognition for enabling safer, more reliable autonomous systems in both planetary and orbital environments.