Konstantinos Kamnitsas
PhD
Associate Professor of Engineering Science
Konstantinos Kamnitsas is Associate Professor of Engineering Science (Medical Imaging) at the Department of Engineering Science and the Institute of Biomedical Engineering (IBME) of the University of Oxford, and Non-Tutorial Fellow at Wolfson College.
He is co-director of the EPSRC CDT in Healthcare Data Science (2024-). His research focuses on Machine-Learning (ML) and primarily deep neural networks for medical image analysis. His work has two main goals:
- Develop reliable, transparent and accountable AI models for safe use in healthcare.
- Empower radiologists, clinicians and researchers with intelligent ML-based tools to better address their research questions and needs of clinical workflows.
Konstantinos completed his PhD at Imperial College London in 2019, where he pioneered development of 3-dimensional neural networks for analysing volumetric medical data, such as MRI and CT, and methods for improving generalization to heterogeneous data. He previously obtained an MSc in Computing Science from Imperial College, and Diploma in Electrical and Computer Engineering from Aristotle University of Thessaloniki, Greece.
He has also conducted research in industry, such as at Microsoft Research and Kheiron Medical Technologies. He became Lecturer at the University of Birmingham in 2021, before moving to Oxford in 2022. His work won various awards, among which international competitions for segmentation of cancer and stroke lesions.
Recent publications
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Radiomics for Treatment Planning in Liver Cancers.
Journal article
Mian A. et al, (2025), JAMA Surg
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As Firm As Their Foundations: Can open-sourced foundation models be used to create adversarial examples for downstream tasks
Conference paper
Hu A. et al, (2025)
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Evaluating Reliability in Medical DNNs: A Critical Analysis of Feature and Confidence-Based OOD Detection
Chapter
Anthony H. and Kamnitsas K., (2025), Lecture Notes in Computer Science, 160 - 170
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Is Your Style Transfer Doing Anything Useful? An Investigation into Hippocampus Segmentation and the Role of Preprocessing
Chapter
Kalabizadeh H. et al, (2025), 15266 LNCS, 155 - 165
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As Firm As Their Foundations: Can open-sourced foundation models be used to create adversarial examples for downstream tasks?
Conference paper
Hu A. et al, (2024)