15 years research and industrial experience in the areas of signal & image processing, machine vision, machine learning, medical image processing, software development, electronic system design, remote sensing, robotic & control systems, and communication systems
Developing machine learning techniques based on advanced image processing and pattern recognition tools for classification of patients diagnosed with breast cancer into low and high risk of tumor recurrence using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and a tumor gene expression assay
Supervised a team of about 50 engineers and technicians in designing, installing, and commissioning industrial communication, control, and automation projects for different shops in a car factory including: Mini Top Coat Paint Shop, PT-ED Paint Shop, Trim Shop
Designed and implemented
•Applied wavelet transform to the Discrete Multitone (DMT) modulation in ADSL (Asymmetric Digital Subscriber Line) modems to improve sample rate, ADSL bit allocation, multiton modulation, channel equalization, Source and channel coding (convolutional codes, Viterbi algorithm), Congestion control in data networks, Speech processing (vocoder), Linear and nonlinear filtering, adaptive filters: LMS, NLMS, DFE, Wiener
Maintained computer network hardware and software
Selected Journal Articles:
[J7]Majid Mahrooghy, Ahmed Ashraf, Dania Daye, Elizabeth McDonald, Mark Rosen, Carolyn Mies, Michael Feldman, and Despina Kontos, “Pharmacokinetic Tumor Heterogeneity as a Prognostic Biomarker for Classifying Breast Cancer Recurrence Risk,” Accepted in IEEE Transaction on Biomedical Engineering
[J6]M. Mahrooghy, A. B. Ashraf, D. Daye, C. Mies, M. Feldman, M. Rosen, D. Kontos, “Heterogeneity Wavelet Kinetics from DCE-MRI for Classifying Gene Expression Based Breast Cancer Recurrence Risk ,” Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013, Lecture Notes in Computer Science Volume 8150, 2013, pp 295-302
[J5]Majid Mahrooghy, Valentine G. Anantharaj, Nicolas H. Younan, Walter A. Petersen, Kuo Lin Hsu, Ali Behrangi, and James Aanstoos, “Augmenting satellite precipitation estimation with lightning information”, International Journal of Remote Sensing, vol.34, no.16, pp. 5796-5811, 2013
[J4] Majid Mahrooghy, Nicolas H. Younan, and Valentine G. Anantharaj, James. Aanstoos “Enhancement of Satellite Precipitation Estimate via Unsupervised Dimensionality Reduction,” IEEE Transactions on Geoscience and Remote Sensing, vol. 50, no.10, pp. 3931 - 3940, 2012.DOI: 10.1109/TGRS.2012.2189406.
[J3]Majid Mahrooghy, Nicolas H. Younan, Valentine G. Anantharaj, J. Aanstoos, and Shantia Yarahmadian “On the Use of the Genetic Algorithm Filter-Based Feature Selection technique for Satellite Precipitation Estimation”, IEEE Geoscience and Remote Sensing Letters, vol. 9, no.5, pp. 963-967, 2012.
[J2]Majid Mahrooghy, Valentine G. Anantharaj, Nicolas H. Younan, J. Aanstoos, and K-L Hsu “On an Enhanced PERSIANN-CCS Algorithm for Precipitation Estimation,” Journal of Atmospheric and Oceanic Technology, vol. 29, no. 7, pp. 922-932, 2012. DOI:10.1175/JTECH-D-11-00146.1.
[J1]Majid Mahrooghy, Nicolas H. Younan, Valentine G. Anantharaj, J. Aanstoos, and Shantia Yarahmadian “On The Use of a Cluster Ensemble Cloud Classification Technique in Satellite Precipitation Estimation”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.5, no.5, pp.1356,1363, 2012.
•Programming language: Matlab, C++, Python, Fortran, Delphi, Visual basic
•Software: SPSS, R, ITK-SNAP, ArcGIS, OrCAD, Pspice
•Libraries: OpenCV, ITK
Companies Worked For:
Job Titles Held: