Dr. Sebelan Danishvar

PhD in Electrical and Computer Engineering

Biography

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.

Education History

PhD in Computer and Electrical Engineering (2007), Tarbiat Modares University - Image processing and analysisThesis: Improving 3D Medical Image Fusion in Brain Tumor Monitoring
M.Sc. in Computer and Electrical Engineering (2003), Tarbiat Modares University - Image processing and analysisThesis: Medical Image Registration and Fusion
B.Sc. in Biomedical Engineering (2001), Shahid Beheshti Medical University - BioelectricDissertation: Design of Electronic Parts of Spectrophotometer

Teaching Experiences

Course Title	Education Level
Course Title	PhD	MSc	BSc
Machine learning	*	*
Neural networks and deep learning	*	*
Advanced image processing	*	*
Biomedical signal processing	*	*
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			*

Interest Area

Machine learning - Artificial neural networks - Deep learning
Research and Development in Image and Signal Processing and Analysis
Medical Signal and Image Analysis and Processing
Image Fusion, Registration, and Segmentation
EEG and ECG Signal Analysis
Feature Extraction, Pattern Recognition, and Classification

Technical Engineering Skills:

Artificial Intelligence (AI) - Deep learning algorithms
Programming languages: Expert in Python and MATLAB and Good Knowledge of C++
Analysis of Big Data
Project Management
Technical Writing

Technical Engineering Skills:

Evaluation of the relationship between the renal ultrasonography and pathological findings in AKI patients using processing of ultrasonic data
Designing Nano scaffolds containing growth factor for stem cell differentiation engineering
Study of Differences between Musicians' and Non-Musicians' Brain Connectivity
Music-evoked emotions classification by EEG Microstates
Automatic Segmentation Staphylococcus Epidermidis Bacteria in Microscopy Images
Edge detection of the image based on matching pursuit algorithm
Extraction of mature oocyte cells structure in mice from microscopy images
The analysis of microarray for classification of effective genes in cancer
Automatic segmentation of multiple sclerosis lesions in brain MRI images based on supervised methods
Structural medical image fusion based on Hilbert transform
Multi-focus image fusion based on integral transforms
PET and MRI image fusion based on multi-scale transforms
Structural and functional images fusion in the diagnosis and evaluation of metastatic bronchogenic carcinoma
Brain MRI Images Segmentation Using Improved FCM Clustering Based on Imperialist Competitive Algorithm
Reversible watermarking of medical image based on ACO
Medical image watermarking with interpolation error technique using an Imperialist competitive algorithm
Face recognition using deformable and non-rigid registration based on geometrical features
PET and MRI images fusion by combining Daubechies wavelet-based fusion method and YCbCr colour space model
MRI and PET images fusion by combining NSCT and YCbCr
Brain image fusion using multi-resolution methods
Dental radiography images registration
Face recognition based on image registration
Multi-focus image fusion using multi-resolution methods
Retinal image registration using active contour
Retinal image registration using geometrical features
Mathematical modelling of a Cardiovascular system for pathophysiological studies.
A system implementation for manufacturing diabetic shoe
Planning for face surgery
Brain topographic mapping by MRI and EEG data fusion

Overall Supervising (Advising) Students Research Experience

Qualifications

Supervisor

(Num. of Students)

Advisor

(Num. of Students)

PhD

MSc

BSc

50+

Publications (Selected Journal Papers)

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.