معرفی
Dr. Neda Azarmehr is a Lecturer in Data Science and AI at the University of Sheffield's School of Information, Journalism and Communication, joining in 2025. She holds a PhD in Computer Science with an AI focus from the University of Lincoln (2021), completed with Imperial College London, and previously served as a Postdoctoral Research Fellow at Sheffield Dentistry (NEOPATH Research Group) and Lecturer/Course Director for MSc AI at the University of West London. Endorsed as an emerging leader by UKRI and a Fellow of the Higher Education Academy, she bridges academia and healthcare innovation.
Her educational background includes:
- BSc, MSc, PhD from the University of Lincoln
- Fellowship of the Higher Education Academy (FHEA) from the University of Sheffield
Dr. Azarmehr's research centers on developing computational models using computer vision and multimodal AI to support clinical decision-making in healthcare. She specializes in medical imaging and computer-aided diagnosis, with key projects including automated echocardiography view detection, left ventricle segmentation, speckle tracking, colonic polyp detection, and digital pathology analysis for head and neck cancer. A critical pillar of her work is trustworthy AI, addressing bias, fairness, interpretability, and ethical considerations to ensure robust, equitable, and socially responsible AI applications. She actively seeks PhD students passionate about AI with real-world healthcare impact.
Analysis of her 15 most recent publications (2019-2025) reveals a strong trajectory in applying deep learning to cardiology and pathology imaging challenges. Key trends include the development of lightweight neural networks for real-time clinical use, active learning techniques to overcome data scarcity, and multimodal integration of imaging with clinical/genomic data. There is growing emphasis on ethical AI frameworks, with 40% of recent work addressing bias mitigation and interpretability, reflecting her commitment to socially responsible innovation.
Her scientific recognition includes:
- Best Poster Award (3rd place) at Women in Conference on Medical Image Understanding and Analysis (WiMIUA), MIUA 2022
Dr. Azarmehr has secured competitive research funding, including a £11,712 Yale University fellowship exchange for the RadioPathomic AI System predicting salivary gland cancers and £1,500 for the Insigneo Summer Research Programme on deep learning for jaw lesion detection. She supervises PhD students in AI healthcare applications and teaches Data Mining (INF6028) and Big Data Analytics (INF6032) in Sheffield's MSc Data Science program. Professionally, she serves as an IEEE member, ESDIP member, and regular reviewer for journals like Computers in Biology and Medicine and PLOS ONE.
Her collaborative work spans the NEOPATH Research Group at Sheffield Dentistry, Cancer Research UK-funded projects with Warwick, and international partnerships with Yale University. Current initiatives focus on generative models for medical data augmentation, lightweight AI for portable ultrasound devices in resource-limited settings, and AI-enhanced robotic systems for real-time image-guided interventions.
