Dr Sareh Rowlands

I am a Senior Lecturer in Data Science in the Department of Computer Science at the University of Exeter. My research focuses on computer vision and machine learning for challenging real-world problems, with a particular interest in trustworthy, uncertainty-aware and robust AI.

A central theme of my research is understanding how AI systems behave when they encounter uncertainty, unfamiliar data, distribution shift or adversarial conditions. I am interested in developing AI systems that can recognise their limitations and can be questioned and scrutinised rather than simply trusted.

My research spans computer vision, machine learning and data science across healthcare, environmental intelligence and robotics. In environmental intelligence, I develop AI methods for biodiversity and ecosystem monitoring, combining camera-trap imagery, remote sensing and environmental data to support species and habitat assessment and management. In healthcare, I develop computer vision and machine learning methods for medical imaging, including paediatric fracture assessment, neuroimaging, digital pathology and antimicrobial resistance. My earlier research focused on computer vision for robotics and video understanding, including human activity recognition, egocentric vision and action anticipation.

I work across disciplines with researchers, clinicians, environmental scientists and other partners to develop and translate AI methods for real-world applications. My research has been supported by UKRI and Innovate UK, and I have worked with partners across healthcare, environmental research and industry.

I am also involved in research leadership and community activities, including serving as Assistant Director of the UKRI Environmental Intelligence Centre for Doctoral Training and as Area Chairs for Computer Vision and Pattern Recognition (CVPR), European Conference on Computer Vision (ECCV) and British Machine Vision Conference (BMVC).

I supervise PhD and postgraduate research across computer vision, trustworthy AI, environmental intelligence, multimodal AI and medical imaging. I welcome enquiries from prospective PhD students and research collaborators interested in reliable and responsible AI for real-world applications.

Research interests

• Computer vision
• Machine learning
• Artificial intelligence
• Trustworthy and responsible AI
• Medical imaging
• Environmental intelligence
• Biodiversity monitoring
• Robotics and autonomous systems
• Egocentric and first-person vision
• Video understanding
• Multimodal AI

Research leadership and service

Assistant Director, UKRI Environmental Intelligence Centre for Doctoral Training

Supporting interdisciplinary doctoral training at the intersection of artificial intelligence, environmental science and data-driven environmental research.

Area Chair, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), European Conference on Computer Vision (ECCV), British Machine Vision Conference (BMVC)

Serving on the programme committee for leading international conferences in computer vision.