Imperial College London


Faculty of MedicineDepartment of Metabolism, Digestion and Reproduction

Senior Data Scientist



+44 (0)20 7594 0759e.angelini CV




Sir Alexander Fleming BuildingSouth Kensington Campus





Elsa D. Angelini is the co-lead of the Data Science Group in Institute of Translational Medicine and Therapeutics (ITMAT) within NIHR Imperial Biomedical Research Centre (BRC).
She is also the co-director of the Heffner Biomedical Imaging Laboratory at Columbia University and is affiliated with the Department of Data-Signal-lmage  at Telecom Paris (Associate Professor / on leave). She has co-authored over 140 peer-reviewed articles and has graduated 19 PhD students. 

She is a Senior Member of IEEE and was the Vice-President for Technical Activities for IEEE EMBS (2017-19).

She is or has served as an Associate Editor for IEEE T-BM, J-BHI, Open EMB, BioImaging journals, and on the steering committee of IEEE T-MI. She is or has been an elected member of several boards (EMBS AdCom, ParisTech AdCom, CNRS INS2I Scientific Advisory Board). She has been on the program committee of MICCAI’07-08-11-12, and  co-chair (2016-19) of the SPIE Medical Imaging Conference on Image Processing. She was on the organizing committee of MICCAI’08 and ISBI’08-21, was he general chair of ISBI’15 in Brooklyn NY and chair of the ISBI Steering Committee (2016-18). She is/was a member (chair 2013-15) of the EMBS TC on Biomedical Imaging and Image Processing (BIIP) and of the SPS TC on BioImaging and Signal Processing (BISP).



Angelini E, Shah A, 2021, Using artificial intelligence in fungal lung disease: CPA CT imaging as an example, Mycopathologia, ISSN:0301-486X

Greenbury SF, Ougham K, Wu J, et al., 2021, Identification of variation in nutritional practice in neonatal units in England and association with clinical outcomes using agnostic machine learning, Scientific Reports, Vol:11, ISSN:2045-2322

Yang G, Chen J, Gao Z, et al., 2020, Simultaneous left atrium anatomy and scar segmentations via deep learning in multiview information with attention, Future Generation Computer Systems: the International Journal of Grid Computing: Theory, Methods and Applications, Vol:107, ISSN:0167-739X, Pages:215-228


Dai C, Wang S, Mo Y, et al., 2020, Suggestive annotation of brain tumour images with gradient-guided sampling, International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), Springer International Publishing, Pages:156-165, ISSN:0302-9743

Barbaroux H, Feng X, Yang J, et al., 2020, Encoding human cortex using spherical CNNs - a study on Alzheimer's disease classification, 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), IEEE, Pages:1322-1325

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