معرفی
Shubhr Singh is a Visiting Professor at Queen Mary University of London's School of Electronic Engineering and Computer Science, based in the Peter Landin building (Room CS 403). His research focuses on artificial intelligence, machine learning, audio signal processing, and their applications in bioacoustics and financial technology. He has contributed to advancements in graph neural networks (GNNs) for audio identification and classification, few-shot learning for bioacoustic event detection, and AI-driven innovations in banking systems.
His work spans interdisciplinary areas such as perceptual music similarity metrics, intelligent audio control systems, and agricultural studies on crop growth optimization. Singh collaborates on international challenges like the DCASE series, exploring cutting-edge methods in sound event detection and domain adaptation.
Key research trends in his publications include leveraging GNNs for complex audio analysis tasks, addressing data scarcity via few-shot learning, and integrating AI into real-world applications like neobanks and agricultural sustainability. His articles reflect a blend of theoretical advancements and practical implementations across diverse domains.
