saba-sadiya [at] em.uni-frankfurt.de
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About
I am an R2 researcher with the Frankfurt Institute of Advanced Studies (FIAS). Currently, I am a member of Dr Gemma Roig's Computational Vision & AI lab, I am also affiliated with Dr Radoslaw Cichy's Neural Dynamics of Visual Cognition lab.
Previously I completed a dual Ph.D in Computer Science under Dr Mohammad Ghassemi, and Cognitive Neuroscience under Dr Taosheng Liu. I earned Bachelors in both Computer Science and Mathematics from the "Technion - Institute of Technology" and subsequently worked as a VLSI engineer at Apple Inc. before becoming a Fulbright grantee in MSU.
My main areas of interest are neural representations, bioinformatics, and digital humanities. My PhD thesis focused on utilizing electroencephalography in conjunction with state-of-the-art machine learning techniques to investigate how attention modulates sensory representations.
I spend the little free time I have learning to play various instruments to various degrees of success.
Project Highlights
Feature Imitating Networks
Novel framework for integrating expert knowledge into deep learning networks by initalizing weights to approximate known statistical measures.
Papers:Feature Imitating Networks In Proceedings of the 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022 S. Saba-Sadiya and T. Alhanai and T. Liu and M. Ghassemi [pdf] [bib] [code]
MambaNet: A Hybrid Neural Network for Predicting the NBA Playoffs Online Preprint, 2022 R. Khanmohammadi, S. Saba-Sadiya and T. Alhanai and T. Liu and M. Ghassemi [pdf] [bib] [code]
Artifact Detection and Correction in EEG Data
Applying state-of-the-art self-supervised machine learning techniques to artifact detection and correction in EEG data.
Papers:Unsupervised EEG Artifact Detection and Correction In Frontiers in Digital Health, Special issue on Machine Learning in Clinical Decision-Making. Volume 2, 2020 S. Saba-Sadiya and E. Chantland and T. Alhanai and T. Liu and M. Ghassemi [pdf] [bib] [code]
EEG Channel Interpolation Using Deep Encoder-Decoder Networks In Proceedings of the 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2020 S. Saba-Sadiya and T. Alhanai and T. Liu and M. Ghassemi [pdf] [bib] [code]