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Oleg  Aslanidi

Dr Oleg Aslanidi

Reader in Biophysical Cardiac Modelling

Biography

Dr Oleg Aslanidi is Reader in the School of Biomedical Engineering & Imaging Sciences and Course Director of Biomedical Engineering BEng/MEng.

Research areas: 

Biophysical modelling, cardiac electrophysiology, atrial fibrillation, thrombogenesis, artificial intelligence

    Research

    AdobeStock_276394749
    Centre for Doctoral Training in Digital Twins for Healthcare

    DT4Health brings together a world-class multidisciplinary team of supervisors to train future innovation leaders to articulate and materialise the Digital Twin vision in healthcare.

    News

    Students rate Biomedical Engineering programme highest at King's and across London

    The Biomedical Engineering BEng/MEng programme has achieved an overall average of 89% positive responses in the National Student Survey (NSS) for 2024.

    NSS 2024

    Biomedical Engineering scores highest rating for an Undergraduate Programme at King's

    The Biomedical Engineering BEng/MEng programme has achieved an overall average of 87% positive responses in the National Student Survey (NSS) for 2023.

    NSS image v2

    AI approach could predict treatment strategy for arrhythmia patients

    The proposed approach is unique in combining patient imaging, image-based modelling and artificial intelligence (AI)

    cardiogram

      Research

      AdobeStock_276394749
      Centre for Doctoral Training in Digital Twins for Healthcare

      DT4Health brings together a world-class multidisciplinary team of supervisors to train future innovation leaders to articulate and materialise the Digital Twin vision in healthcare.

      News

      Students rate Biomedical Engineering programme highest at King's and across London

      The Biomedical Engineering BEng/MEng programme has achieved an overall average of 89% positive responses in the National Student Survey (NSS) for 2024.

      NSS 2024

      Biomedical Engineering scores highest rating for an Undergraduate Programme at King's

      The Biomedical Engineering BEng/MEng programme has achieved an overall average of 87% positive responses in the National Student Survey (NSS) for 2023.

      NSS image v2

      AI approach could predict treatment strategy for arrhythmia patients

      The proposed approach is unique in combining patient imaging, image-based modelling and artificial intelligence (AI)

      cardiogram