معرفی
Dr. Ivor Simpson is an Associate Professor in Informatics at the University of Sussex, affiliated with the School of Engineering and Informatics and part of the AI research group. He serves as the Academic Lead for Sussex AI and convenes the MRes in Advanced Artificial Intelligence. His academic career includes prior roles as a Senior Lecturer (2022–present) and Lecturer (2020–2022) in Artificial Intelligence at the same institution.
His educational background includes a DPhil in Medical Image Analysis from the University of Oxford (2008–2012) and an MEng in Computer Science from the University of Southampton (2004–2008). Prior to his academic appointments, he worked as a Senior Research Scientist and Head of Machine Learning at Anthropics Technology (2014–2019) and as a Research Associate at University College London (2012–2014).
Ivor’s research lies at the intersection of machine learning and applied statistics, with a focus on probabilistic modeling for imaging and temporal data. His work emphasizes uncertainty quantification, interpretable AI, and deep generative models, applied to medical image analysis, computer vision, and ecological monitoring. He is particularly interested in inverse problems, morphometry, image registration, and multi-modal MRI analysis.
His recent publications (2022–2025) reflect a strong trend toward uncertainty-aware models in medical imaging, ecoacoustics, and computer vision. Topics include compressed sensing MRI, variational autoencoders, deep ensembles, and interactive ecoacoustic dashboards. These works demonstrate interdisciplinary collaboration and methodological innovation, particularly in quantifying spatial uncertainty and building interpretable representations.
- MICCAI Young Scientist Award (2013) for work on probabilistic non-linear registration
Dr. Simpson actively supervises students, currently serving as primary supervisor for 6 PhD candidates and secondary supervisor for several others. He has led or participated in multiple research grants from EPSRC, NERC, and Innovate UK, supporting projects in ecoacoustics, MRI modeling, and machine learning applications. His teaching includes advanced machine learning, computer vision, and the MRes in Advanced AI. He leads a research team focused on interdisciplinary AI applications and collaborates widely across academia and industry.
