PhD, FHEA
Lecturer in Artificial Intelligence
School of Engineering, Computing and Mathematics, University of Plymouth
Dr Vivek Singh is a Lecturer in Artificial Intelligence at the School of Engineering, Computing and Mathematics, University of Plymouth. He leads teaching and supervision across undergraduate and postgraduate AI programmes, equipping students with the theoretical foundations and practical expertise needed to address real-world, high-impact AI challenges.
His research centres on data-efficient, resource-aware, and multimodal learning, with a focus on developing intelligent systems that perform robustly under limited labelled data and constrained computational environments. He designs scalable learning frameworks that bridge methodological innovation with deployment readiness, targeting applications in medical imaging, visual scene understanding, video analytics, and complex real-world perception systems.
Prior to academia, Dr Singh held industry roles ranging from AI Researcher to Senior Research Engineer, delivering machine vision and image processing solutions across applied AI projects. His PhD research focused on deep learning architectures for human facial expression analysis and model optimisation. Following his doctorate, he served as a Research Fellow at the Visual Artificial Intelligence Lab at Oxford Brookes University, further advancing research in computer vision and applied AI systems.
Developing data-efficient and resource-efficient models for spatio-temporal data analysis, such as images and videos. The research focuses on improving predictive performance while reducing data requirements and computational cost, enabling deployment in real-world and resource-constrained applications.
Designing algorithms that enable AI systems to retain knowledge when learning from new data. Focuses is also on integrating complementary signals such as vision, language, audio, and other modalities. Aim is to build richer representations, improve generalisation, and support adaptable AI systems that can evolve over time.
Applying AI to high value domains such as human activity analysis, surgical workflow analysis, and biomedical image understanding. Emphasis is on robustness, interpretability, and reliability, with the goal of developing AI systems that can support decision-making in safety-critical environments.
Research: Assessment of Brain Tumours Using Machine Learning and MRI Radiomics
Research: Multimodal AI-based Diagnosis of Autism Spectrum Disorder (ASD)
PhD Student
SECAM, University of Plymouth
Research: Exploration of incremental knowledge addition for human activity analysis in open-world scenarios for public safety and surveillance
PhD Student (Co-supervised)
Peninsula Medical School, University of Plymouth
Research: Ergonomic challenges facing general surgeons and strategies to reduce the risk of work-related musculoskeletal disorders
