Mohsi Jawaid

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About

Mohsi Jawaid is a researcher at the forefront of neuromorphic vision and spacecraft pose estimation, a critical area for autonomous satellite operations and in-orbit servicing. His most significant contribution is the creation of **SEENIC**, a pioneering dataset for Spacecraft posE Estimation with NeuromorphIC vision. This work directly addresses the challenge of bridging the space domain gap by providing synchronized event streams and ground truth camera poses across 20 distinct scenes. By leveraging the high temporal resolution and low latency of event-based cameras, Jawaid’s dataset enables robust satellite pose estimation even under challenging lighting and high-speed motion conditions typical of space. While his work is still early in its citation lifecycle (with 2 citations for the SEENIC dataset), its foundational nature—being the first of its kind—positions it as a critical resource for future research in autonomous spacecraft navigation. Jawaid’s contributions are paving the way for safer, more reliable satellite operations through neuromorphic sensing, making him a key emerging voice in the intersection of computer vision and space technology.