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
OXSeg: Multidimensional Attention UNet-Based Lip Segmentation Using Semi-Supervised Lip Contours.
Journal article
Moghaddasi H. et al, (2025), IEEE Access, 13, 104075 - 104088
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 Trans Biomed Eng, 71, 3324 - 3336
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)
Classification of De novo post-operative and persistent atrial fibrillation using multi-channel ECG recordings.
Journal article
Moghaddasi H. et al, (2022), Comput Biol Med, 143
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), 1155 - 1159
Imaging of heart acoustic based on the sub-space methods using a microphone array.
Journal article
Moghaddasi H. et al, (2017), Comput Methods Programs Biomed, 146, 133 - 142