Dr Saideh Ferdowsi
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Email
s.ferdowsi@essex.ac.uk -
Telephone
+44 (0) 1206 874384
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Location
3A.532, Colchester Campus
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Academic support hours
Wednesday 4-5 pm & Friday 11-12 am on campus/zoom to be confirmed in advance via email.
Profile
Biography
Dr Saideh Ferdowsi is a lecturer (assistant professor) in data science at the School of Mathematics, Statistics and Actuarial Science, University of Essex. She received her PhD from the University of Surrey in biomedical signal and image processing in 2013. After completing PhD, she started working at University of Shahrood as an assistant professor and then in 2019, she joined brain computer interface lab at University of Essex as a senior research officer. Her primary research focuses on neural data analysis and she has developed different algorithms to analyse neural signals and images including EEG, fMRI, MRS and fNIRS. These techniques have been used for different purposes such as artifact removal, feature extraction, data fusion, estimating the model, and measuring brain connectivity. Dr Ferdowsi is a senior member of the Institute of Electrical and Electronics Engineers (IEEE). She has been one of the guest editors of the International Journal of Biomedical Imaging and Sensors Journal. In addition, she is a reviewer of various conferences and journals such as Neuroimage, Scientific Reports, IEEE Transactions on Biomedical Engineering, IEEE Transactions on Signal Processing, IEEE Transactions on Neural System and Rehabilitation Engineering, Signal Image and Video Processing, Biomedical Signal Processing and Control, IET signal processing, and IET Image processing. Prospective PhD applicants who have related research interests are encouraged to contact her by email.
Qualifications
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PhD University of Surrey,
Appointments
University of Essex
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Lecturer in Statistics and Data Science, Mathematical Science, University of Essex (1/4/2023 - present)
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Senior Research Officer, Computer Science and Electrical Engineering, University of Essex (1/7/2019 - 31/3/2023)
Other academic
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Lecturer in Biomedical Engineering, University of Shahrood (1/1/2013 - 30/6/2019)
Research and professional activities
Research interests
Computational neuroscience
Using machine learning methods to analyse neural data including EEG, fMRI, fNIRS, EOG, EMG, ECG, MRS,....
Brain Connectivity
Investigating functional and effective brain connectivity using methods such as graph theory, dynamic causal model and granger causality.
Deep Learning application in neuroscience
Blind Source Seperation for biomedical data analysis
Brain Computer Interface
Physiological signal Processing
Teaching and supervision
Current teaching responsibilities
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Mathematics Careers and Employability (MA199)
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Artificial intelligence and machine learning with applications (MA336)
Current supervision
Publications
Journal articles (18)
Ferdowsi, S., Foulsham, T., Rahmani, A., Ognibene, D., Citi, L. and Li, W., (2025). Identifying the human olfactory and chemosignaling neural networks using event related fMRI and graph theory. Scientific Reports. 15 (1), 12000-
Abolghasemi, V., Marzebali, MH. and Ferdowsi, S., (2022). Recursive Singular Spectrum Analysis for Induction Machines Unbalanced Rotor Fault Diagnosis. IEEE Transactions on Instrumentation and Measurement. 71, 1-11
Ameri, R., Alameer, A., Ferdowsi, S., Nazarpour, K. and Abolghasemi, V., (2022). Labeled projective dictionary pair learning: application to handwritten numbers recognition. Information Sciences. 609, 489-506
Marzebali, MH., Abolghasemi, V., Ferdowsi, S. and Bazghandi, R., (2022). Manipulation of stator current signature for rotor asymmetries fault diagnosis of wound rotor induction machine. IET Science, Measurement & Technology. 16 (9), 523-532
Ghonchi, H., Fateh, M., Abolghasemi, V., Ferdowsi, S. and Rezvani, M., (2020). Deep recurrent–convolutional neural network for classification of simultaneous EEG–fNIRS signals. IET Signal Processing. 14 (3), 142-153
Ferdowsi, S. and Abolghasemi, V., (2018). Multi layer spectral decomposition technique for ERD estimation in EEG μ rhythms: An EEG–fMRI study. Neurocomputing. 275, 1836-1845
Abolghasemi, V., Chen, M., Alameer, A., Ferdowsi, S., Chambers, J. and Nazarpour, K., (2018). Incoherent Dictionary Pair Learning: Application to a Novel Open-Source Database of Chinese Numbers. IEEE Signal Processing Letters. 25 (4), 472-476
Ferdowsi, S. and Abolghasemi, V., (2018). Simultaneous BOLD detection and incomplete fMRI data reconstruction. Medical & Biological Engineering & Computing. 56 (4), 599-610
Ferdowsi, S. and Abolghasemi, V., (2018). Semiblind Spectral Factorization Approach for Magnetic Resonance Spectroscopy Quantification. IEEE Transactions on Biomedical Engineering. 65 (8), 1717-1724
Ferdowsi, S., Sanei, S. and Abolghasemi, V., (2015). A Predictive Modeling Approach to Analyze Data in EEG–fMRI Experiments. International Journal of Neural Systems. 25 (01), 1440008-1440008
Abolghasemi, V., Ferdowsi, S. and Sanei, S., (2015). Fast and incoherent dictionary learning algorithms with application to fMRI. Signal, Image and Video Processing. 9 (1), 147-158
Abolghasemi, V. and Ferdowsi, S., (2015). EEG–fMRI: Dictionary learning for removal of ballistocardiogram artifact from EEG. Biomedical Signal Processing and Control. 18, 186-194
Ferdowsi, S., Abolghasemi, V. and Sanei, S., (2015). A new informed tensor factorization approach to EEG–fMRI fusion. Journal of Neuroscience Methods. 254, 27-35
Sanei, S., Ferdowsi, S., Nazarpour, K. and Cichocki, A., (2013). Advances in Electroencephalography Signal Processing [Life Sciences]. IEEE Signal Processing Magazine. 30 (1), 170-176
Ferdowsi, S., Sanei, S., Abolghasemi, V., Nottage, J. and O'Daly, O., (2013). Removing Ballistocardiogram Artifact From EEG Using Short- and Long-Term Linear Predictor. IEEE Transactions on Biomedical Engineering. 60 (7), 1900-1911
Sanei, S., Ferdowsi, S., Nazarpour, K. and Cichocki, A., (2013). Advances in Electroencephalography Signal Processing [Life Sciences].. IEEE Signal Process. Mag.. 30, 170-176
Abolghasemi, V., Ferdowsi, S. and Sanei, S., (2012). A gradient-based alternating minimization approach for optimization of the measurement matrix in compressive sensing. Signal Processing. 92 (4), 999-1009
Abolghasemi, V., Ferdowsi, S. and Sanei, S., (2012). Blind Separation of Image Sources via Adaptive Dictionary Learning. IEEE Transactions on Image Processing. 21 (6), 2921-2930
Book chapters (1)
Cervera-Torres, S., Minissi, ME., Greco, A., Callara, A., Ferdowsi, S., Citi, L., Maddalon, L., Giglioli, IAC. and Alcañiz, M., (2023). Modulating Virtual Affective Elicitation by Human Body Odors: Advancing Research on Social Signal Processing in Virtual Reality. In: Lecture Notes in Computer Science. Springer Nature Switzerland. 317- 327. 9783031350160
Conferences (22)
Ghonchi, H., Foulsham, T. and Ferdowsi, S., Assessing Neural Patterns of Anxiety Using Deep Learning: An EEG Study
Ghonchi, H., Foulsham, T. and Ferdowsi, S., (2024). Assessing Neural Patterns of Anxiety Using Deep Learning: An EEG Study
Ferdowsi, S., Ognibene, D., Foulsham, T., Greco, A., Callara, AL., Cervera-Torres, S., Alcañiz, M., Vanello, N. and Citi, L., (2023). Human body odour modulates neural processing of faces: effective connectivity analysis using EEG
Ghonchi, H., Ferdowsi, S. and Abolghasemi, V., (2022). Common Spatial Pattern with Deep Learning for Fetal Heart Rate Monitoring
Ameri, R., Alameer, A., Ferdowsi, S., Abolghasemi, V. and Nazarpour, K., (2021). Classification of Handwritten Chinese Numbers with Convolutional Neural Networks
Ghonchi, H., Fateh, M., Abolghasemi, V., Ferdowsi, S. and Rezvani, M., (2020). Spatio-temporal deep learning for EEG-fNIRS brain computer interface
Ferdowsi, S., Ognibene, D., Foulsham, T., Abolghasemi, V., Li, W. and Citi, L., (2020). Human Chemosignals Modulate Interactions Between Social and Emotional Brain Areas
Abolghasemi, V. and Ferdowsi, S., (2017). Singular value thresholding for multi-dimensional data: Application to fMRI and terahertz imaging
Abolghasemi, V., Ferdowsi, S., Hao Shen, Yaochun Shen and Lu Gan, (2014). Spatio-spectral data reconstruction in terahertz imaging
Ferdowsi, S., Abolghasemi, V. and Sanei, S., (2013). EEG-FMRI integration using a partially constrained tensor factorization
Ferdowsi, S., Sanei, S., Nottage, J., O'Daly, O. and Abolghasemi, V., (2012). A hybrid ICA-Hermite transform for removal of Ballistocardiogram from EEG
Ferdowsi, S., Abolghasemi, V. and Sanei, S., (2012). Blind separation of ballistocardiogram from EEG via short-and-long-term linear prediction filtering
Abolghasemi, V., Ferdowsi, S., Makkiabadi, B. and Sanei, S., (2012). Adaptive fusion of dictionary learning and multichannel BSS
Abolghasemi, V., Ferdowsi, S. and Sanei, S., (2011). Sparse multichannel source separation using incoherent K-SVD method
Ferdowsi, S., Abolghasemi, V., Makkiabadi, B. and Sanei, S., (2011). A new spatially constrained NMF with application to fMRI
Ferdowsi, S., Abolghasemi, V. and Sanei, S., (2011). A comparative study of α-divergence based NMF techniques for fMRI analysis
Ferdowsi, S., Abolghasemi, V. and Sanei, S., (2010). A constrained NMF algorithm for bold detection in fMRI
Abolghasemi, V., Ferdowsi, S., Makkiabadi, B. and Sanei, S., (2010). On optimization of the measurement matrix for compressive sensing
Abolghasemi, V., Sanei, S., Ferdowsi, S., Ghaderi, F. and Belcher, A., (2009). Segmented compressive sensing
Ferdowsi, S., Abolghasemi, V., Ahmadyfard, A. and Sanei, S., (2009). An improved eye detection method based on statistical moments
Abolghasemi, V., Sanei, S., Ferdowsi, S., Ghaderi, F. and Belcher, A., (2009). SEGMENTED COMPRESSIVE SENSING
Ferdowsi, S. and Ahmadyfard, A., (2008). Using statistical moments as invariants for eye detection
Reports and Papers (1)
Ameri, R., Alameer, A., Ferdowsi, S., Nazarpour, K. and Abolghasemi, V., (2020). Classification of Chinese Handwritten Numbers with Labeled Projective Dictionary Pair Learning
Contact
Academic support hours:
Wednesday 4-5 pm & Friday 11-12 am on campus/zoom to be confirmed in advance via email.
