Selina Chu

Papers

Total Citations

170

H-Index

About

Selina Chu is a researcher whose work bridges robotics, audio processing, and computer vision, with a focus on enabling machines to perceive and understand their environments. Her key research areas include acoustic scene recognition for mobile robots and shape-based retrieval for medical applications. Chu’s most impactful contribution is her pioneering work on using audio features for automatic environment classification, as demonstrated in her highly cited 2006 paper "Where am I? Scene Recognition for Mobile Robots using Audio Features" (151 citations). This work established audio as a complementary modality to vision, allowing robots to recognize unstructured environments through characteristic sounds—a significant step toward richer, more robust robotic perception. She further advanced this line of inquiry in a related study on content analysis for acoustic environment classification. Beyond audio, Chu contributed to medical imaging with work on efficient rotation-invariant shape retrieval, addressing challenges in robotic surgery and cell analysis. Her research, though concentrated in the mid-2000s, has left a lasting impact on the fields of mobile robotics and multimodal sensing, inspiring subsequent work on auditory scene understanding.