Soosan Beheshti

Professor
Department of Electrical and Computer Engineering
Ryerson University
Tel:  416-9795000-ext 4906
Fax:  416-9795280
Email: soosan "at" ee.ryerson.ca

 


Teaching

Ryerson University:

·  EE8102 Statistical Inference (Signal Detection Theory) [Graduate Level Course]

·  ELE532/BME532 Signals and Systems I (Lectures Notes + Interactive GUIs)

·  ELE632/BME632 Signals and Systems II

·  ELE639/BME639 Control Systems

Massachusetts Institute of Technology:

·  6.341 Discrete Signal Processing(semesters during 2002-2004)

Teaching Awards

  • Dean’s Teaching Award, Faculty of Engineering, Architecture and Science, Ryerson (2010)
  • EECS Carlton E. Tucker Award for Teaching Excellence, MIT (1998)

Research Interests

·  Statistical Signal Processing

·  Statistical Learning Theory and Generalization

·  Information Theory

·  Data Denoising

·  Data Compression

·  System Modeling and Control

 

Research Laboratory: Signal and Information Processing (SIP) Lab

Location: ENG403, Ryerson University Engineering

 

SIP LAB conducts research in the broad areas of statistical signal processing theory and information theory, with focus on detection theory, learning from data, data denoising and compression, and model order(complexity) detection/selection. We develop theories and algorithms for applications in data modeling and information extraction. Our methods have been applied in various areas such as biomedical signal and image processing, power spectrum estimation, and hyperspectral imaging.  


Publications

Journal Articles:

  • S. Beheshti, E. Nidoy, and F. Rahman “K-MACE and Kernel K-MACE clustering”, IEEE Access, vol. 8, pp. 17390-17403, 2020.  
  • S. Asadizadeh, T. Yousefi, S. Beheshti, A. Delpak, and S. Meshgini “A systematic review of EEG source localization techniques and their applications on diagnosis of brain abnormalities”, Journal of Neuroscience Methods, https://doi.org/10.1016/j.jneumeth.2020.108740s, 2020.  
  • S. Ghanbari Azar, S. Meshgini, T. Yousefi Rezaii and S. Beheshti “ Hyperspectral Image Classification Based on Sparse Modeling of Spectral Blocks”, to appear in Neurocomputing, Elsevier 2020.  
  • E. Naghsh, M. F. Sabahi, and S. Beheshti, “Joint Preprocessing of Multiple Datasets to Enhance Source Separation”, IEEE Signal Processing Letters, vol. 26, no. 12, pp. 1917-1921, 2019.  
  • E. Naghsh, M.F. Sabahi, and S. Beheshti, “ Spatial Analysis of EEG Signals for Parkinson's Disease Stage Detection ”, Signal, Image and Video Processing (SIVP) , vol. 14, Issue 2, pp. 397-405, 2020. 
  • S. Beheshti and S. Sedghizadeh, “Number of Source Signal Estimation by Mean Squared Eigenvalue Error (MSEE)”, IEEE Transactions on Signal Processing, vol. 66, no. 21, pp. 5694-5704, 2018.   (MATLAB Code)
  • S. Eftekharifar, T. Yousefi, S. Beheshti, S. Daneshvar, “Block Sparse Multi-lead ECG Compression Exploiting between-lead Collaboration”, IET Signal Processing vol 13, pp. 46-55, 2019.  
  • S. Beheshti, A. Sahebalam and E. W. Nidoy, “Structure Dependent Weather Normalization”, Energy Science & Engineering, DOI: 10.1002/ese3.272, Wiley, 2019.  
  • S. Sedghizadeh and S. Beheshti, “Data-driven Subspace Predictive Control: Stability and Horizon Tuning”, Journal of the Franklin Institute, vol. 355, Issue 15, pp. 7509-7547, 2018.  
  • S. Sedghizadeh and S. Beheshti, “Particle swarm optimization based fuzzy gain scheduled subspace predictive control”, Engineering Applications of Artificial Intelligence, Elsevier vol. 67, pp. 331-344, 2018.  
  • T. Yousefi, S. Beheshti, M. Shamsi, and S. Eftekharifar, “ECG signal compression and denoising via optimum sparsity order selection in compressed sensing framework”, Biomedical Signal Processing and Control, Elsevier, vol. 41, pp. 161-171, 2018.  
  • Y. Naderahmadian, S. Beheshti, and M. Tinati, “Correlation Based Online Dictionary Learning Algorithm”, IEEE Transactions on Signal Processing, vol. 64, no.3, pp. 592-602, 2016.  
  • M. Shahbaba and S. Beheshti, “ Signature Test as Statistical Testing in Clustering ”, Signal, Image and Video Processing (SIVP) , 2016. 
  • M. Sharifymoghaddam, S. Beheshti, P. Elahi, and M. Hashemi, “Similarity Validation Based Nonlocal Means Image Denoising”, IEEE Signal Processing Letters, vol. 22, no. 12, pp. 2185-2188, Dec. 2015.  
  • S. Pouryazdian, S. Beheshti and S. Krishnan, “ PARAFAC model order detection based on Reconstruction Error in the presence of Kronecker structured colored noise”, Digital Signal Processing no. 48, pp. 12-26, 2016. 
  • Y. Naderahmadian, M. Tinati and S. Beheshti, “ Generalized Adaptive Weighted Recursive Least Squares Dictionary Learning”, Signal Processing, vol. 118, pp. 89-96, January 2016. 
  • M. Hashemi, S. Beheshti, R. S.C. Cobbold, and N. Paul, “ Subband Dependent Compressed Sensing in Local CT Reconstruction ”, Signal, Image and Video Processing (SIVP) , vol. 10, Issue 6, pp. 1009-1015, September 2016. 
  • M. Hashemi, S. Beheshti, R. S.C. Cobbold, and N. Paul, “ Adaptive updating of regularization parameters ”, Signal Processing, vol. 113, pp. 228-233, August 2015. 
  • M. Rasooli, F.H. Foomany, K. Balasundaram, S. Masse, N. Zamiri, A. Ramadeen, X. Hu, P. Dorian, K. Nanthakumar, S. Krishnan, S. Beheshti, K. Umapathy, “ Analysis of Electrocardiogram Pre-shock Waveforms During Ventricular Fibrillation ”, Biomedical Signal Processing and Control Journal, Volume 21, Pages 26-33, August 2015. 
  • S. Hashemi, S. Beheshti, P. Gill, N. Paul and R. Cobbold, “ Accelerated Compressed Sensing Based CT Image Reconstruction ”, Computational and Mathematical Methods in Medicine, vol. 2015, Article ID 161797, 16 pages, 2015. 
  • S. Hashemi Amroabadi, N. Paul, S. Beheshti and R. Cobbold, “ Adaptively Tuned Iterative Low Dose CT Image Denoising ”, Computational and Mathematical Methods in Medicine, vol. 2015, Article ID 638568, 12 pages, 2015. 
  • M. Shahbaba and S. Beheshti, “MACE-means Clustering”, Signal Processing,, vol. 105, pp. 216-225, December 2014. 
  • M. Hashemi and S. Beheshti, “Adaptive Bayesian Denoising for General Gaussian Distributed (GGD) Signals”, IEEE Transactions on Signal Processing, vol. 62 , no.5, pp. 1147-1156, March 2014. 
  • T. Yousefi, S. Beheshti, and M. Tinati, “Efficient LED-SAC Sparse Estimator Using Fast Sequential Adaptive Coordinate-Wise Optimization (LED-2SAC)”, Mathematical Problems in Engineering, vol. 2014, Article ID 317979, 8 pages, doi:10.1155/2014/317979, 2014. 
  • S. Cakir, T. Aytac, A. Yildirim, S. Beheshti, O. N. Gerek, and A. E. Cetin, “Salient point region covariance descriptor for target tracking”, Optical Engineering 52(2):027207:1-13, 2013. 
  • T. Yousefi, M. Tinati, and S. Beheshti, “Adaptive Efficient Sparse Estimator Achieving Oracle Properties”, IET Signal Processing, vol. 7, no. 4, pp. 259-268, 2013. 
  • M. Farzam, S. Beheshti and M. Hashemi, “ Adaptive noise variance estimation and intrinsic order selection for low SNR hyperspectral signals”, Canadian Journal of Electrical and Computer Engineering, vol.36 , no.1, pp. 4-10, 2013. 
  • T. Yousefi, M. Tinati, and S. Beheshti, “Sparsity aware consistent and high precision variable selection”, Signal, Image and Video Processing, Vol. 8, Issue 8, pp. 1613-1624, Nov. 2014. 
  • M. Farzam and S. Beheshti, “ Simultaneous Denoising and Intrinsic Order Selection in Hyperspectral Imaging ”, IEEE Transactions on Geoscience and Remote Sensing, vol. 49, no. 9, pp. 3423-3436, Sept. 2011
  • S. Beheshti, M. Hashemi, E. Sejdic, and T. Chau , “Mean square error estimation in thresholding”, IEEE Signal Processing Letters, vol. 18, no. 2, pp. 103-106, Feb. 2011
  • S. Beheshti, M.Ravan, J. P. Reilly, and L. J. Trainor, “Mean square error in periodogram approaches with adaptive windowing”,   IEEE Transactions on Signal Processing, vol. 59, no. 3, pp. 923-935, March 2011.
  • S. Beheshti, M.Hashemi, X.P.Zhang, and N.Nikvand, “Noisy invalidation denoising”,  IEEE Transactions on Signal Processing, vo. 58, no. 12, December 2010.
  • S. Beheshti,and M.A. Dahleh, “Noisy data and impulse response estimation”,  IEEE Transactions on Signal Processing, vol. 58, no. 2, pp. 510-521, Feb. 2010.
  • M. Hashemi and S. Beheshti, “Adaptive noise variance estimation in BayesShrink”, IEEE Signal Processing Letters, vol. 17, no. 1, pp. 12-15, Jan. 2010.
  • S. Beheshti, A. Fakhrzadeh, and S. Krishnan, “Noiseless codelength in wavelet denoising”, EURASIP Journal on Advances in Signal Processing, vol. 2010, Article ID 641842,  2010.
  • M. Farzam and S. Beheshti, “Endmember transformation and replacement in real time hyperspectral unmixing”, International Journal of Circuits, and Systems, and Signal Processing,  vol.3, pp 181-189, 2009.
  • S. Beheshti and M.A. Dahleh, “A new information theoretic approach to signal denoising and best basis selection”, IEEE Transactions on Signal Processing, vol 53, no. 10, pp. 3613-3624,  Oct. 2005.
  • S. Beheshti, S. H. Isabelle and G. W. Wornell, “Joint intersymbol and multiple-access interference suppression algorithms for CDMA systems”, European Transactions on Telecommunications, Special Issue on Code-Division Multiple-Access Techniques for Wireless Communication Systems, vol. 9, no. 5, pp 403-418, Sept./Oct. 1998 (Invited paper).

Conference Papers:

  • F. Nassif, T. Yousefi Rezaii, and S. Beheshti, “ Pole-Zero REM Modeling with Application in EEG Artifact Removal”,   42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'20), 2020.
  • M. Shamsi, T. Yousefi Rezaii, and S. Beheshti, “ MNDL Sparsity Order Selection in Compressed Sensing”,   42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'20), 2020.
  • Y. Sadatnejad and S. Beheshti, “ Higher Resolution sLORETA (HR-sLORETA) in EEG Source Imaging”,   41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'19), 2019.
  • M.Shamsi, F. Rahman, and S. Beheshti, “ Correct Number of Clusters (CNC) Description Length in Arbitrary Shape Clustering”,   16th Canadian Workshop on Information Theory (CWIT 2019) (Invited paper), 2019.
  • Y. Sadatnejad and S. Beheshti, “ Automated EEG Source Error Thresholding (AESET) in L2-Regularization Inverse Problems”,   16th Canadian Workshop on Information Theory (CWIT 2019), 2019.
  • F. Rahman and S. Beheshti, “Kernel K-mace Clustering”, Asilomar Conference on Signals, Systems and Computers (ACSSC), 2018.
  • Y. Naderahmadian and S. Beheshti, “Generalized adaptive weighted recursive least squares dictionary learning for Retinal vessel inpainting”, IEEE Statistical Signal Processing Workshop (SSP), 2018.
  • S. Sedghizadeh and S. Beheshti, “Fuzzy Gain Scheduling of Subspace Predictive Controller”, American Control Conference (ACC), 2016.
  • S. Pouryazdian, A. Chang, D. Bosnyak, L. J. Trainor, S. Beheshti, S. Krishnan, “ Multi-Domain Feature Selection in Auditory MisMatch Negativity Via PARAFAC-Based Template Matching Approach”,   38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'16), 2016.
  • A. Sahebalam, S. Beheshti, W. Khreich, and E. W. Nedoy “A Novel Approach in Household Electricity Consumption Forecasting”,   29th Canadian Conference on Electrical and Computer Engineering (CCECE), 2016.
  • S. Beheshti and A. Sahebalam, “ Reconstruction-Error Distortion in LTI system modeling”,   29th Canadian Conference on Electrical and Computer Engineering (CCECE), 2016.
  • A. Sahebalam and S. Beheshti, “ Approximated Capacity Region of Gaussian Multiple-Access Relay Channel with Correlated Noises”,   IEEE Radio & Wireless Week (RWW2016), 2016.
  • S. Pouryazdian, S. Beheshti, S. Krishnan, and T Bastos, “ Localization of Brain Activities using Multiway Analysis of EEG Tensor Via EMD and Reassigned TF Representation”,   37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'15), 2015.
  • R. Godinez Tello, S. Pouryazdian, A. Ferreira, S. Beheshti, S. Krishnan, and T Bastos, “A New Approach for SSVEP Detection Using PARAFAC and Canonical Correlation Analysis ”,   37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'15), 2015.
  • S. Pouryazdian,S. Beheshti, and S. Krishnan, “Multi-way based Source Localization of Multichannel EEG signals Exploiting Hilbert-Huang Transform ”,   World Congress (WC2015) on Medical Physics and Biomedical Engineering., 2015.
  • Assad Sahebalam and S. Beheshti, “Gaussian Multiple-Access Relay Channels with Non-Causal Side Information at the Transmitters ”,   14th Canadian Workshop on Information Theory(CWIT15), 2015.
  • Assad Sahebalam and S. Beheshti, “ Competitive Clustering of Wireless Sensor Networks with Ultra-Wideband Multiple-Access Relay Channel”,   28th Canadian Conference on Electrical and Computer Engineering (CCECE), 2015.
  • Y. Naderahmadian and S. Beheshti, “ A Realistic Attack on SVD Based Watermarking Scheme Scaling Attack”,   28th Canadian Conference on Electrical and Computer Engineering (CCECE), 2015.
  • Y. Naderahmadian and S. Beheshti, “ Robustness of Wavelet Domain Watermarking Against Scaling Attack”,   28th Canadian Conference on Electrical and Computer Engineering (CCECE), 2015.
  • M. Hashemi, Sh. Khayyer, A. Quach, H. Farooq, A. Bargriz Farshi, and S. Beheshti, “Electron Microscopy Image Restoration and Resolution Improvement using an Example-based Super-Resolution Algorithm ”,   Biomedical Engineering Society (BMES), 2014.
  • M. Hashemi, S. Beheshti, R. S.C. Cobbold, and N. Paul, “ Non-Local Total Variation based Low-Dose Computed Tomography Denoising”,   36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'14), 2014.
  • M. Shahbaba and S. Beheshti, “Efficient Unimodality Test In Clustering By Signature Testing”,   IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014.
  • P. Elahi, S. Beheshti, and M. Hashemi, “BM3D MRI denoising equipped with Noise Invalidation technique”,   IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014.
  • M. Shahbaba and S. Beheshti, “Model Verification of GMM Clustering Based on Signature Testing”,   27th Canadian Conference on Electrical and Computer Engineering (CCECE), 2014.
  • Rasooli M, Foomany FH, Balasundaram K, Masse S, Zamiri N, Ramadeen A, Hu X, Dorian P, Nanthakumar K, Beheshti S, Umapathy K., “ Blind source separation in characterizing ECG pre-shock waveforms during ventricular fibrillation.”,   35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'13), 2013.
  • M. Hashemi, S. Beheshti, P. R. Gill, N. Paul, and R. S.C. Cobbold, “Fast Fan/Parallel Beam CS-Based Low-Dose CT Reconstruction”,   IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013.
  • S. Mostafaei, B. Wu and S. Beheshti, “A Novel Hybrid Active Anti-Islanding Method For Multi-Converter Fed Distributed Generation Systems”,   14th IEEE International Conference on Industrial Technology (ICIT 2013), 2013.
  • A. Karami, S. Beheshti, M. Yazdi, and R. Moghaddam, “Hyperspectral Image Compression Using 3d Discrete Cosine Transform and Support Vector Machine Learning”,   11th International Conference on Information Science, Signal Processing and Their Applications (ISSPA), 2012.
  • M. Shahbaba and S. Beheshti, “Improving X-means Clustering with MNDL”,   11th International Conference on Information Science, Signal Processing and Their Applications (ISSPA), 2012.
  • S. Pouryazdian, S. Beheshti, and S. Krishnan, “Minimum Noiseless Description Length (MNDL) Based Regularization Parameter Selection”,   11th International Conference on Information Science, Signal Processing and Their Applications (ISSPA), 2012.
  • M. Farzam and S. Beheshti, “Robust hyperspectral signal unmixing in the presence of correlated noise”,   IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011.
  • M. Hashemi and S. Beheshti, “Adaptive Image Denoising by Rigorous BayesShrink Thresholding”,   IEEE International Workshop on Statistical Signal Processing 2011 (SSP'11), 2011.
  • M. Ravan and S.Beheshti, “Speech recognition from adaptive windowing PSD estimation”,   24th Canadian Conference on Electrical and Computer Engineering (CCECE), 2011.
  • M.Farzam and S.Beheshti, “Information Theoretic Assessment of Correlated Noise in Hyperspectral Signal Unmixing”,   24th Canadian Conference on Electrical and Computer Engineering (CCECE), 2011.
  • M. Hashemi and S. Beheshti, “Retrieving quantized signal from its noisy version”, IEEE workshop on Signal Processing Systems(SiPS), 2010.
  • M. Hashemi, S. Beheshti, and M. Farzam, “Two stage quantization of noisy hyperspectral images”,  Queen’s Biennial Symposium on Communications (QBSC), 2010.
  • M.Farzam and S. Beheshti, “The noiseless codelength concept in subspace estimation for low SNR hyperspectral signals”,   IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PacRim),   (Gold Paper Award Winner) 2009.
  • M.Farzam and S.Beheshti, “A Noiseless codelength  method to estimate dimensionality of hyperspectral data”,  IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2009.
  • M. Farzam and S. Beheshti, “Fast transition and replacement (FTR) algorithm for real time hyperspectral imaging applications”, International Conference on Remote Sensing (Best Paper), 2008.
  • S. Beheshti, “Kullback-Leibler Distance in parametric modeling”,  IEEE international Symposium on Information Theory (ISIT), 2008.
  • M. Farzam, S.Beheshti, and  K. Raahemifar, “Calculation of abundance factors in hyperspectral imaging using genetic algorithms”, Canadian Conference on Electrical and Computer Engineering (CCECE), 2008.
  • S. Beheshti and M. Ravan, “Adaptive windowing in nonparameteric power spectral density estimation”, Canadian Conference on Electrical and Computer Engineering (CCECE), 2008.
  • N. Nikvand, S. Beheshti, and X. Fernando, “Soft thresholding by noise invalidation”, Queen’s Biennial Symposium on Communications (QBSC), 2008.
  • S. Beheshti, “Data compression and linear modeling”,Data Compression Conference (DCC), 2008.
  • S. Beheshti and S. Pal, “A new approach to nonparametric PSD estimation and optimum windowing”, International Conference on Digital Signal Processing (DSP), 2007.
  • A. Fakhrzadeh and S. Beheshti, “Minimum noiseless description length (MNDL) thresholding”, IEEE Symposium on Computational Intelligence in Image and Signal Processing (CIISP), 2007.
  • S. Pal and S. Beheshti, “A new look at frequency resolution in power spectral density estimation”, IEEE Symposium on Computational Intelligence in Image and Signal Processing (CIISP), 2007.
  • S. Beheshti, “A new approach to order selection and parametric spectrum estimation”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), vol. 3, pp. 520-523, 2006.
  • S. Beheshti and M.A. Dahleh, “LTI systems, additive noise and order estimation”, IEEE Conference on Decision and Control (CDC), 2003.
  • S. Beheshti and M.A. Dahleh, “New information theoretic approach to order estimation problem”, IFAC Symposium on System Identification, 2003.
  • S. Beheshti and M.A. Dahleh, “A new minimum description length”, American Control Conference (ACC), 2003.
  • S. Beheshti and M.A. Dahleh, “Noise variance in signal denoising”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2003.
  • S. Beheshti and M.A. Dahleh, “On denoising and signal representation”, Mediterranean Conference on Control and Automation, 2002.
  • S. Beheshti and M.A. Dahleh, “On choice of impulse response length in channel identification”, IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PacRim), 2001.
  • S. Beheshti and M.A. Dahleh, “On model quality evaluation of stable LTI systems”,  IEEE Conference on Decision and Control (CDC), 2000.
  • S. Beheshti and G. W. Wornell, “Iterative interference cancellation and decoding for spread-signature CDMA systems”, IEEE Vehicular Technology Conference (VTC), 1997.

Members of Signal and Information Processing (SIP) Lab

  • Soosan Beheshti (Director)
  • Farah Nassif (Accelerated MASc Student)
  • Ishtiaque Ahmed (MASc Student)
  • Mahdi Shamsi (PhD Student)
  • Yasser Ali (PhD Student, co-supervising with Dr. Farrokh Sharifi)
  • Erfan Naghsh (Research Assistant)

Alumni

  • Younes Sadat-Nejad (MASc)- PhD Student University of Toronto
  • Saba Sedghizadeh (PhD) Research Assistant, Ryerson University
  • Edward Nidoy (MASc )- Analog Layout Designer, AMD, Canada
  • Faizan Rahman (MASc)- Research Assistant Ryerson University
  • Soufia Naseri (MEng)
  • Erfan Naghsh (Visiting PhD), PhD student Esfahan University
  • Asad Sahebalam (PostDoc)-Data Scientist, Developer, and Researcher, Screaming Power, Canada
  • Mehdi Shahbaba (PhD)- Senior Data Scientist, RBC, Canada
  • Yashar Naderahmadian (Visiting PhD, Tabriz University)
  • Mina Sharifymoghaddam (MASc)- Site Reliability, Thomson Reuters, Canada
  • Hossain Rahnamaee (MASc)
  • Saeed Pouryazdian (PhD, co-supervised with Dr. Sri Krishnan)- Machine Learning Software Developer, TELUS
  • Sasan Mostafaei (MASc, co-supervised with Dr. Bin Wu) - Danfoss VLT Drives
  • Masoud Hashemi (MASc) - PhD, University of Toronto- Machine Learning Specialist, Xanadu, Canada
  • Richard Sun (MASc, co-supervised with Dr. Venkatesh)- Developer at SAP, UofT, Canada
  • Tohid Yousefi (visiting PhD Student)- Faculty of University of Tabriz
  • Pegah Elahi (MASc, Linkoping University) Data Analyst at Altus Group
  • Marzieh Rasooli - Serior Solution Specialist, SAS, Canada
  • Masoud Farzam (PhD)- Lecturer and Laboratory Coordinator, UOIT
  • Nima Nikvand  (MASc)- PhD, Waterloo University-Design Engineer at Sartrex, Canada
  • Azadeh Fakhrzadeh (MASc)- PhD Student, Uppsala University
  • Mohammad Rahman (MEng) March Consulting Associates
  • Maryam Ravan  (Postdoctoral Research Assistant)- Assistant Professor, New York Institute of Technology, NY