Prof. O’Connor’s early research was in the field of video compression, specifically object-based compression in the context of MPEG-4, which subsequently led to an interest in video object segmentation and tracking as well as other aspects of computer vision. Following the advent of MPEG-7, he became interested in audio-visual (AV) analysis for content-based information retrieval as well as low-power configurable hardware for AV processing. As his research became increasingly multi-disciplinary he developed research interests in the Internet of Things, including both instrumented environments and next generation wearable sensors. The focus of his current research is in multi-modal content analysis leveraging mutually complementary sensor data sources, for applications in sports and health, digital media, ambient assisted living and environmental monitoring.