Dr. Sebelan Danishvar received the PhD in Electrical and Computer Engineering in 2008. He has been an academic board for more than 10 years. His expertise is in Artificial intelligence and Machine learning (Deep learning, human-centred AI, reinforcement learning, and the theoretical foundations of ML), Data Analytics, Signal and Image Processing and Analysis (Image fusion and registration), Computer and Machine Vision algorithms (Develop image recognition and computer vision applications), Spectral Analysis in industry and medical field. He has a vast experience in Python, Matlab and C++ programming software.
Course Title |
Education Level |
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---|---|---|---|
PhD |
MSc |
BSc |
|
Machine learning |
* |
* |
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Neural networks and deep learning |
* |
* |
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Advanced image processing |
* |
* |
|
Biomedical signal processing |
* |
* |
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Wavelet and application in signal and image processing |
* |
* |
|
Programming: Python (or Matlab) |
|
* |
* |
Physiology |
|
* |
* |
Anatomy |
|
* |
* |
Digital design |
|
|
* |
Engineering statistics and probabilities |
|
|
* |
Electronics |
|
|
* |
Electrical Circuits |
|
|
* |
Engineering mathematics |
|
|
* |
Mathematics |
|
|
* |
Radiology |
|
|
* |
Qualifications |
Supervisor (Num. of Students) |
Advisor (Num. of Students) |
---|---|---|
PhD |
3 |
6 |
MSc |
33 |
20 |
BSc |
50+ |
50+ |
B Masoudi, S Danishvar, SN Razavi, “Multi-modal neuroimaging feature fusion via 3D Convolutional Neural Network architecture for schizophrenia diagnosis”, Intelligent Data Analysis 25 (3), 527-540, 2021.
M Danishvar, S Danishvar, F Souza, P Sousa, A Mousavi, “Coarse Return Prediction in a Cement Industry’s Closed Grinding Circuit System through a Fully Connected Deep Neural Network (FCDNN) Model”, Applied Sciences 11 (4), 1361, 2021.
B Masoudi, S Danishvar, SN Razavi, “A Multi-Modal Fusion of Features Method Based on Deep Belief Networks to Diagnosis Schizophrenia Disease”, International Journal of Wavelets, Multiresolution and Information Processing, DOI: 10.1142/S0219691320500885
M. Khorrampanah, H. Seyedarabi, S. Danishvar, M. Farhoudi, “Optimization of montages and electric currents in tDCS”, Computers in Biology and Medicine, 2020.
V. Vasilakia, S.Danishvar, A. Mousavi, E. Katsou,” Data-driven versus conventional N2O EF quantification methods in wastewater; how can we quantify reliable annual EFs?” Computers & Chemical Engineering, June 2020.
M. Moghaddari, M. Zolfy, S. Danishvar, M. Zolfy, “Diagnose ADHD Disorder in Children using Convolutional Neural Network based on Continuous Mental Task EEG,” Computer Methods and Programs in Biomedicine, 2020.
B. Masoudi, S. Danishvar, N. Razavi, “Multi-Modal schizophrenia disorder diagnosis via a GRU-CNN architecture,” International Journal of Pattern Recognition and Artificial Intelligence, 2020.
R. Arvanaghi, S. Daneshvar, H. Seyedarabi, A. Goshvarpour, “Fusion of ECG and ABP signals based on wavelet transform for cardiac arrhythmias classification,” Computer Methods and Programs in Biomedicine, Vol. 151, pp. 71-78, 2017.
A. Goshvarpour, A. Abbasi, A. Goshvarpour, S. Daneshvar, “Discrimination between different emotional states based on the chaotic behaviour of galvanic skin responses”, Signal, Image and Video Processing, Vol. 11, No. 7, pp 1347–1355, 2017.
M. Samiei, Z. Aghazadeh, E. D. Abdolahinia, A. Vahdati, S. Daneshvar and A. Noghani, “The effect of electromagnetic fields on survival and proliferation rate of dental pulp stem cells,” Acta Odontologica Scandinavica, Published online: 19 Mar 2020, DOI: 10.1080/00016357.2020.1734655
S. Asadzadeh, S. Daneshvar, B. Abedi, B. S. Oskouei, P. Shahabi, Y. Jasemian, “An advanced algorithm for the description of mice oocyte cytoplasm and polar body”, Biomedical Signal Processing and Control, Vol. 48, pp. 171-178, 2019.
T. Akbarpour, M. Shamsi, S. Daneshvar, M. Poureisa, “Fusion of multimodal medical images using nonsubsampled shearlet transform and particle swarm optimization,” Multidimensional Systems and Signal Processing, 2019.
T. Akbarpour, M. Shamsi, S. Daneshvar, M. Poureisa, “Medical image fusion based on nonsubsampled shearlet transform and principal component averaging” International Journal of Wavelets, Multiresolution and Information Processing, Vol. 17, No. 4, pp.19-26, 2019.
H. Shiri, M. A. Tinati, M. Codreanu, S. Daneshvar, “Distributed Sparse Diffusion Estimation based on Set Membership and Affine Projection Algorithm,” Digital Signal Processing, Vol. 73, pp. 47-61, 2018.
S. Eftekharifar, T.Y. Rezaii, S. Beheshti, S. Daneshvar, “Block Sparse multi-lead ECG Compression Exploiting between-lead Collaboration,” IET Signal Processing, 2018.
B. Nobariyan, N. Amini, S. Daneshvar, A Abbasi, “A Novel Architecture of Medical Image Fusion based on YCbCr – DWT Transform” International Arab Journal of Information Technology, Vol. 15, No. 5, pp. 850-856, 2018.
H. T. Khosroshahi, B. Abedi, S. Daneshvar, E. Alizadeh, M. Khalilzadeh, Y. Abedi, “Cross-linked Polyelectrolyte and Its Function in Adsorption of Fluid and Excess Nitrogen Waste Products: an Experimental Study on Dialysate Effluent Fluid”, Iranian journal of kidney diseases, Vol. 11, No. 4, pp. 294-303, 2017.
S. Gharebaghi, S. Daneshvar, M.H. Sedaaghi, “Retinal Image Registration Using Geometrical Features,” Journal of Digital Imaging, Vo. 26, No. 2, pp.248-258, 2013.
MA. Bakhshali, M. Mafi, S. Daneshvar, “Mathematical modelling of the patent ductus arteriosus (PDA),” Mathematical and Computer Modelling of Dynamical Systems, Vol. 19, No. 3, pp. 238-249, 2013.
M. Dousty, S. Daneshvar, M. Haghjoo, “The effects of sedative music, arousal music and silence on electrocardiography signals,” Journal of Electrocardiology, Vol. 44, pp.396.e1–396.e6, 2011.
S. Daneshvar, H. Ghassemian, “MRI and PET image fusion by combining IHS and retina-inspired models,” Information Fusion, Elsevier, Vol. 11, No. 2, pp. 114-123, 2010.
S. Daneshvar, H. Ghassemian, “MRI and PET images fusion based on human retina model”, Journal of Zhejiang University SCIENCE A, Vol.8, No.10, pp.1624-1632, 2007.