Hanie Moghaddasi
B.Sc, M.Sc, Ph.D
Postdoctoral Researcher in Machine Learning and Biomedical Imaging
- Postdoctoral researcher
Biography
I studied biomedical engineering for my B.Sc. and M.Sc. at Amirkabir University of Technology. In 2019, I started my Ph.D. at Delft University of Technology (TU Delft), where I worked on the severity detection of atrial fibrillation from multi-modal analysis. Currently, I'm a postdoctoral researcher in machine learning and biomedical imaging at the Nuffield Department of Women's & Reproductive Health. I'm mostly focused on defining translational approaches for identifying Fetal Alcohol Spectrum Disorder (FASD). This project aims to develop a machine learning algorithm to assist clinicians with identifying FASD using 3D facial image analysis and neurocognitive performance metrics.
Recent publications
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A Singular-value-based Map to Highlight Abnormal Regions Associated with Atrial Fibrillation Using High-resolution Electrograms and Multi-lead ECG
Journal article
Moghaddasi H. et al, (2024), IEEE Transactions on Biomedical Engineering, 1 - 13
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Novel Rank-based Features of Atrial Potentials for the Classification Between Paroxysmal and Persistent Atrial Fibrillation
Conference paper
Moghaddasi H. et al, (2022), Computing in Cardiology Conference (CinC)
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Classification of De novo post-operative and persistent atrial fibrillation using multi-channel ECG recordings
Journal article
Moghaddasi H. et al, (2022), Computers in Biology and Medicine, 143, 105270 - 105270
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Tensor-based Detection of Paroxysmal and Persistent Atrial Fibrillation from Multi-channel ECG
Conference paper
Moghaddasi H. et al, (2021), 2020 28th European Signal Processing Conference (EUSIPCO)
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Imaging of heart acoustic based on the sub-space methods using a microphone array
Journal article
Moghaddasi H. et al, (2017), Computer Methods and Programs in Biomedicine, 146, 133 - 142
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Automatic assessment of mitral regurgitation severity based on extensive textural features on 2D echocardiography videos
Journal article
Moghaddasi H. and Nourian S., (2016), Computers in Biology and Medicine, 73, 47 - 55