Adel Elmaghraby

Director of Research and Innovation

Adel S. Elmaghraby, an IEEE Life Senior Member, is the Speed School Director of Industrial Research and Innovation and Winnia Professor of CSE and former chairman of the Computer Engineering and Computer Science Department at the University of Louisville. He has also held appointments at Carnegie Mellon's Software Engineering Institute and the University of Wisconsin-Madison, and has advised over 60 master's graduates and 24 doctoral graduates. His research and publications span intelligent systems, neural networks, cyber-security, visualization and simulation. The IEEE-Computer Society has recognized his work with multiple awards including a Golden Core membership.

Education

B.S. in Computer Science, Alexandria University, 1973
M.S. in Electrical Engineering, University of Wisconsin-Madison, 1978
Ph.D. in Electrical Engineering, University of Wisconsin-Madison, 1982

Publications

Detection of Volatile Compounds Emitted by Bacteria in Wounds Using Gas Sensors- 2019

In this paper we analyze an experiment for the use of low-cost gas sensors intended to detect bacteria in wounds using a non-intrusive technique. Seven different genera/species of microbes tend to be present in most wound infections. Detection of these bacteria usually requires sample and laboratory testing which is costly, inconvenient and time-consuming. The validation processes for these sensors with nineteen types of microbes (1 , 2 , 6 , 1 , 1 , 2 and 6 ) are presented here, in which four sensors were evaluated: TGS-826 used for ammonia and amines, MQ-3 used for alcohol detection, MQ-135 for CO₂ and MQ-138 for acetone detection. Validation was undertaken by studying the behavior of the sensors at different distances and gas concentrations. Preliminary results with liquid cultures of 10⁸ CFU/mL and solid cultures of 10⁸ CFU/cm of the 6 strains revealed that the four gas sensors showed a response at a height of 5 mm. The ammonia detection response of the TGS-826 to showed the highest responses for the experimental samples over the background signals, with a difference between the values of up to 60 units in the solid samples and the most consistent and constant values. This could suggest that this sensor is a good detector of , and the recording made of its values could be indicative of the detection of this species. All the species revealed similar CO₂ emission and a high response rate with acetone for , and .

Journal Articles
- Elmaghraby, A., S. (2021). Editorial: Enabling Wearable Brain Technologies - Methods and Applications. Frontiers in Human Neuroscience
- Dekhil, O., Ali, M., Elnakieb, Y., Shalaby, A., Soliman, A., Switala, A., Mahmoud, A., Ghazal, M., Hajjdiab, H., Casanova, M., F., Elmaghraby, A., S., Keynton, R., S., El-Baz, A., S. & Barnes, G., N. (2020). A Personalized Autism Diagnosis CAD System Using a Fusion of Structural MRI and Resting-State Functional MRI Data. Frontiers in Psychiatry, 10
- Elmaghraby, A., S. (2021). Breast Lesions Detection and Classification via YOLO-Based Fusion Models. Computers, Materials & Continua
- Baccouche, A., Ahmed, S., Sierrasosa, D., E. & Elmaghraby, A., S. (2020). Malicious Text Identification: Deep Learning from Public Comments and Emails. Information
- Telahun, M., Sierrasosa, D., E. & Elmaghraby, A., S. (2020). Heuristic Analysis for In-Plane Non-Contact Calibration of Rulers Using Mask R-CNN. Information
- Baccouche, A., Garcia Zapirain Soto, M., B., Olea, C., C. & Elmaghraby, A., S. (2020). Ensemble Deep Learning Models for Heart Disease Classification: A Case Study from Mexico. Information
- Elmaghraby, A., S. (2021). IoT in Smart Cities: A Survey of Technologies, Practices and Challenges. Smart Cities
- Elmaghraby, A., S. (2021). A novel technology to integrate imaging and clinical markers for non-invasive diagnosis of lung cancer. Scientific Reports
- Elmaghraby, A., S. (2021). Diabetes Type 2: Poincare Data Preprocessing for Quantum Machine Learning. Computers, Materials & Continua
- Elmaghraby, A., S. (2021). Exploiting Deep Learning Techniques for Colon Polyp Segmentation. Computers, Materials & Continua
- Aliradi, R., Belkhir, A., Ouamane, A. & Elmaghraby, A., S. (2018). DIEDA: discriminative information based on exponential discriminant analysis combined with local features representation for face and kinship verification. Multimedia Tools and Applications, 1--18
- Reda, I., Khalil, A., Elmogy, M., Abou El-Fetouh, A., Shalaby, A., Abou El-Ghar, M., Elmaghraby, A., S., Ghazal, M. & El-Baz, A., S. (2018). Deep Learning Role in Early Diagnosis of Prostate Cancer. Technology in cancer research & treatment, 17, 1533034618775530
- Shaffie, A., Soliman, A., Fraiwan, L., Ghazal, M., Taher, F., Dunlap, N., Wang, B., van Berkel, V., Keynton, R., S., Elmaghraby, A., S. & El-Baz, A., S. (2018). A Generalized Deep Learning-Based Diagnostic System for Early Diagnosis of Various Types of Pulmonary Nodules. Technology in Cancer Research & Treatment, 17, 1533033818798800
- Sierra-Sosa, D., Tebaldi, M., Grumel, E., Rabal, H. & Elmaghraby, A., S. (2018). Localized analysis of paint-coat drying using dynamic speckle interferometry. Optics and Lasers in Engineering, 106, 61--67
- Garcia-Zapirain, B., Shalaby, A., El-Baz, A., S. & Elmaghraby, A., S. (2017). Automated framework for accurate segmentation of pressure ulcer images. Computers in biology and medicine, 90, 137--145
- Losavio, M., M. & Elmaghraby, A., S. (2017). Security and the Transnational Information Polity. Journal of Digital Forensics, Security and Law, 12(3), 67--76
- Zheng, Y., Blasch, E., P., Elmaghraby, A., S., Zheng, Y., F., Blasch, E. & Elmaghraby, A., S. (2016). Biologically Inspired Methods for Imaging, Cognition, Vision, and Intelligence. Computational Intelligence and Neuroscience, 2016, 2402067
- McClure, P., Khalifa, F., Soliman, A., Abou El-Ghar, M., Gimelfarb, G., Elmaghraby, A., S. & El-Baz, A., S. (2014). A Novel NMF Guided Level-Set for DWI Prostate Segmentation. Journal of Computer Science & System Biology, 7(6), 209–216
- Sliman, H., Elnakib, A., Beache, G., Elmaghraby, A., S. & El-Baz, A., S. (2014). Assessment of Myocardial Function from Cine Cardiac MRI using A Novel 4D Tracking Approach. Journal of Computer Science & System Biology, 7(5), 169-173
- Elmaghraby, A., S., El-Baz, A., S., Firjani, A., Elnakib, A., Khalifa, F., Gimel'farb, G., Abou El-Ghar, M. & Gimel’farb, G. (2013). A diffusion-weighted imaging based diagnostic system for early detection of prostate cancer. Journal of Biomedical Science and Engineering, 6, 346-356
- Sliman, H., Khalifa, F., Elnakib, A., Soliman, A., El-Baz, A., Beache, G., Elmaghraby, A. & Gimel'farb, G. (2013). Myocardial borders segmentation from cine MR images using bidirectional coupled parametric deformable models. MEDICAL PHYSICS, 40(9)
- Abbaschian, B., J., Sierra-Sosa, D. & Elmaghraby, A. (2021). Deep Learning Techniques for Speech Emotion Recognition, from Databases to Models. Sensors (Basel, Switzerland), 21(4)
- Ahmed, S., Gentili, M., Sierra-Sosa, D., Elmaghraby, . & S., A. (2022). Multi-layer data integration technique for combining heterogeneous crime data. Information Processing & Management, 59(3)
- Asghari, M., Nielsen, J., Gentili, M., Koizumi, N. & Elmaghraby, A. (2022). Classifying Comments on Social Media Related to Living Kidney Donation: Machine Learning Training and Validation Study. JMIR Medical Informatics, 10(11), e37884
- Asghari, M., Sierra-Sosa, D. & Elmaghraby, A., S. (2022). BINER: A low-cost biomedical named entity recognition. Information Sciences, 602, 184--200
- Baccouche, A., Garcia-Zapirain, B. & Elmaghraby, A. (2022). An integrated Framework for Breast Mass Classification and Diagnosis using Stacked Ensemble of Residual Neural Networks. Scientific Reports, 12, 1--17
- Baccouche, A., Garcia-Zapirain, B., Castillo Olea, C. & Elmaghraby, A., S. (2021). Connected-UNets: a deep learning architecture for breast mass segmentation. NPJ breast cancer, 7(1), 151
- Baccouche, A., Garcia-Zapirain, B., Zheng, Y. & Elmaghraby, A., S. (2022). Early detection and classification of abnormality in prior mammograms using image-to-image translation and YOLO techniques. Computer Methods and Programs in Biomedicine, 221, 106884
- Bouzid, A., Sierra-Sosa, D. & Elmaghraby, A. (2022). Directional Statistics-Based Deep Metric Learning for Pedestrian Tracking and Re-Identification. Drones, 6(11), 328
- Sleman, A., A., Soliman, A., Elsharkawy, M., Giridharan, G., Ghazal, M., Sandhu, H., Schaal, S., Keynton, R., Elmaghraby, A. & El-Baz, A. (2021). A novel 3D segmentation approach for extracting retinal layers from optical coherence tomography images. Medical physics, 48(4), 1584-1595
- Syed, A., S., Sierra-Sosa, D., Kumar, A. & Elmaghraby, A. (2021). A Hierarchical Approach to Activity Recognition and Fall Detection Using Wavelets and Adaptive Pooling. Sensors (Basel, Switzerland), 21(19)
- Syed, A., S., Sierra-Sosa, D., Kumar, A. & Elmaghraby, A. (2022). A deep convolutional neural network-xgb for direction and severity aware fall detection and activity recognition. Sensors, 22(7), 2547
- Syed, A., S., Sierra-Sosa, D., Kumar, A. & Elmaghraby, A. (2022). Making Cities Smarter—Optimization Problems for the IoT Enabled Smart City Development: A Mapping of Applications, Objectives, Constraints. Sensors, 22(12), 4380
- Asghari, M., Sierra-Sosa, D. & Elmaghraby, A., S. (2020). A topic modeling framework for spatio-temporal information management. Information processing & management, 57(6), 102340
- Asghari, M., Sierrasosa, D., E., Telahun, M., Kumar, A. & Elmaghraby, A., S. (2020). Aggregate density-based concept drift identification for dynamic sensor data models. Journal of Neural Computing and Applications
- Blasch, E., P. & Elmaghraby, A., S. (2015). Biologically Inspired Methods for Imaging Cognition Vision and Intelligence. Biologically Inspired Methods for Imaging Cognition Vision and Intelligence, 154816
- Casanova, M., F., Konkachbaev, A., I., Switala, A., E. & Elmaghraby, A., S. (2008). Recursive trace line method for detecting myelinated bundles: a comparison study with pyramidal cell arrays. Journal of neuroscience methods, 168(2), 367-72
- Dekhil, O., Ali, M., El-Nakieb, Y., Shalaby, A., Soliman, A., Switala, A., Mahmoud, A., Ghazal, M., Hajjdiab, H., Casanova, M., F., Elmaghraby, A., Keynton, R., El-Baz, A. & Barnes, G. (2019). A Personalized Autism Diagnosis CAD System Using a Fusion of Structural MRI and Resting-State Functional MRI Data. Frontiers in psychiatry, 10, 392
- Dekhil, O., Shalaby, A., Soliman, A., Mahmoud, A., Kong, M., Barnes, G., Elmaghraby, A. & El-Baz, A. (2021). Identifying brain areas correlated with ADOS raw scores by studying altered dynamic functional connectivity patterns. Medical image analysis, 68, 101899
- Elmaghraby, A., S. (2015). Visual Data Analytics for an Event City. Visual Data Analytics for an Event City, 6
- Garcia-Zapirain, B., Sierra-Sosa, D., Ortiz, D., Isaza-Monsalve, M. & Elmaghraby, A. (2018). Efficient use of mobile devices for quantification of pressure injury images. Technology and health care : official journal of the European Society for Engineering and Medicine, 26(S1), 269-280
- García-Zapirain, B., Elmogy, M., El-Baz, A. & Elmaghraby, A., S. (2018). Classification of pressure ulcer tissues with 3D convolutional neural network. Medical & biological engineering & computing, 56(12), 2245-2258
- Habas, P., A., Zurada, J., M., Elmaghraby, A., S. & Tourassi, G., D. (2006). Probabilistic framework for reliability analysis of information-theoretic CAD systems in mammography. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 1, 6113-6
- Kantardzic, M., M., Aly, A., A. & Elmaghraby, A., S. (1999). Visualization of neural-network gaps based on error analysis. IEEE transactions on neural networks, 10(2), 419-26
- Khalifa, F., Soliman, A., Elmaghraby, A., Gimel'farb, G. & El-Baz, A. (2017). 3D Kidney Segmentation from Abdominal Images Using Spatial-Appearance Models. Computational and mathematical methods in medicine, 2017, 9818506
- Khalil, M., H., Azab, M., Elsayed, A., Sheta, W., Gabr, M. & Elmaghraby, A., S. (2019). MAINTAINING CLOUD PERFORMANCE UNDER DDOS ATTACKS. International Journal of Computer Networks & Communications (IJCNC), 11(6)
- McClure, P., Elnakib, A., Abou El-Ghar, M., Khalifa, F., Soliman, A., El-Diasty, T., Suri, J., S., Elmaghraby, A. & El-Baz, A. (2014). In-vitro and in-vivo diagnostic techniques for prostate cancer: a review. Journal of biomedical nanotechnology, 10(10), 2747-77
- Patino-Barrientos, S., Sierra-Sosa, D., Garcia-Zapirain, B., Castillo-Olea, C. & Elmaghraby, A. (2020). Kudo’s Classification for Colon Polyps Assessment Using a Deep Learning Approach. Applied Sciences, 10(2), 501
- Shaffie, A., Soliman, A., Mahmoud, A., Ghazal, M., Hajjdiab, H., Keynton, R., Giridharan, G., Elmaghraby, A., Suri, J., S. & El-Baz, A. (2019). Lung Nodule Classification Based on the Integration of a Higher-Order Markov-Gibbs Random Field Appearance Model and Geometric Features. Lung Imaging and CADx, 203
- Shehata, M., Shalaby, A., Mahmoud, A., Ghazal, M., Hajjdiab, H., Badawy, M., A., El-Ghar, M., A., Bakr, A., M., Dwyer, A., C., Keynton, R. & others, . (2019). Towards Big Data in Acute Renal Rejection. Big Data in Multimodal Medical Imaging, 205--223
- Sierra-Sosa, D., Arcila-Moreno, J., Garcia-Zapirain, B., Castillo-Olea, C. & Elmaghraby, A. (2020). Dementia prediction applying variational quantum classifier. arXiv preprint arXiv:2007.08653
- Sierra-Sosa, D., Garcia-Zapirain, B., Castillo, C., Oleagordia, I., Nuno-Solinis, R., Urtaran-Laresgoiti, M. & Elmaghraby, A., S. (2019). Scalable Healthcare Assessment for Diabetic Patients Using Deep Learning on Multiple GPUs. IEEE Transactions on Industrial Informatics, 15(10), 5682-5689
- Sierra-Sosa, D., Garcia-Zapirain, B., Castillo, C., Oleagordia, I., Nu~no-Solinis, R., Urtaran-Laresgoiti, M. & Elmaghraby, A. (2019). Scalable Healthcare Assessment for Diabetic Patients Using Deep Learning on Multiple GPUs. IEEE Transactions on Industrial Informatics, 15(10), 5682--5689
- Sliman, H., Khalifa, F., Elnakib, A., Soliman, A., El-Baz, A., Beache, G., M., Elmaghraby, A. & Gimel'farb, G. (2013). Myocardial borders segmentation from cine MR images using bidirectional coupled parametric deformable models. Medical physics, 40(9), 092302
- Soliman, A., Khalifa, F., Shaffie, A., Mahmoud, A., Dunlap, N., Wang, B., Elmaghraby, A., Gimel’farb, G., Keynton, R., Ghazal, M. & others, . (2019). Early Assessment of Radiation-Induced Lung Injury. Lung Imaging and CADx, 349--370
- Sánchez-González, A., García-Zapirain, B., Sierra-Sosa, D. & Elmaghraby, A. (2018). Automatized colon polyp segmentation via contour region analysis. Computers in biology and medicine, 100, 152-164
- Zahia, S., Garcia Zapirain Soto, M., B. & Elmaghraby, A. (2020). Integrating 3D Model Representation for an Accurate Non-Invasive Assessment of Pressure Injuries with Deep Learning. Sensors (Basel, Switzerland), 20(10)
- Zahia, S., Sierra-Sosa, D., Garcia-Zapirain, B. & Elmaghraby, A. (2018). Tissue classification and segmentation of pressure injuries using convolutional neural networks. Computer methods and programs in biomedicine, 159, 51-58
- Shaffie, A., Soliman, A., Mahmoud, A., Khalifeh, H., A., Taher, F., Ghazal, M., Elmaghraby, A. & El-Baz, A. (2019). Early diagnosis system for lung nodules based on the integration of a higher-order MGRF appearance feature model and 3D-CNN. Lung Cancer and Imaging, 1-1 to 1-22
- Zahia, S., Garcia Zapirain Soto, M., B., Sevillano, X., González, A., Kim, P. & Elmaghraby, A., S. (2020). Pressure injury image analysis with machine learning techniques: A systematic review on previous and possible future methods. Artificial Intelligence in Medicine
- Elmaghraby, A., S. (2021). Poincare sphere noise filtering for singularities in dynamic speckle activity: Application to paint drying time measurement. Optics and Lasers in Engineering
- Sierrasosa, D., E., Telahun, M. & Elmaghraby, A., S. (2020). TensorFlow Quantum: Impacts of Quantum State Preparation on Quantum Machine Learning Performance. IEEE Access
- Kandil, H., Soliman, A., Ghazal, M., Mahmoud, A., Shalaby, A., Keynton, R., Elmaghraby, A., S., Giridharan, G., A. & El-Baz, A., S. (2019). A Novel Framework for Early Detection of Hypertension using Magnetic Resonance Angiography. Scientific Reports, vol. 9(1), 11105
Books
- Abdelwahab, O. & Elmaghraby, A., S. (2016). UofL at SemEval-2016 Task 4: Multi Domain word2vec for Twitter Sentiment Classification. (p.169-175). San Diego: Association for Computational Linguistics

More about Adel Elmaghraby

- Certificates of Appreciation, 2014, ABET- CSAB
- Certificate of Appreciation, 2014, Corporate Security Symposium
- Community Engagement Awards, 2013, University of Louisville
- NSA Colloquium CNSS 2013 Awards, 2013, The Committee on National Security Systems (CNSS)
- Recognition, 2012, IEEE
- Service Excellence Award, 2012, AEAS
- Distinguished Service Award, 2010, IEEE Louisville Section
- Sevice Recognition, 2019, Association of Egyptian American Scholars
2023
Spring
- CSE 622 - SIMUL/DISCRETE SYSTEMS
- CSE 622 - SIMUL/DISCRETE SYSTEMS
2022
Spring
- CSE 622 - SIMUL/DISCRETE SYSTEMS
- CSE 622 - SIMUL/DISCRETE SYSTEMS
Summer
- CSE 590 - SPECIAL TOPICS - CECS
Fall
- CSE 545 - ARTIFICIAL INTELLIGENCE
- CSE 545 - ARTIFICIAL INTELLIGENCE
- CSE 545 - ARTIFICIAL INTELLIGENCE
- CSE 545 - ARTIFICIAL INTELLIGENCE
2021
Spring
- CSE 622 - SIMUL/DISCRETE SYSTEMS
- CSE 593 - IND STUDY IN CECS
- CSE 622 - SIMUL/DISCRETE SYSTEMS
Fall
- CSE 694 - SP TOP-CSE
- CSE 694 - SP TOP-CSE
2020
Spring
- CECS 622 - SIMUL/DISCRETE SYSTEMS
- CECS 796 - INDEPENDENT STUDY IN CSE
- CECS 622 - SIMUL/DISCRETE SYSTEMS
Fall
- CSE 694 - SP TOP-CSE
- CSE 694 - SP TOP-CSE
2019
Spring
- CECS 795 - SEM IN COMPUTER & ENG
- CECS 696 - CECS PROJECT
- CECS 694 - SP TOP-CECS
- CECS 568 - COMPUTER FORENSICS
- CECS 799 - DISSERTATION RESEARCH
- CECS 795 - SEM IN COMPUTER & ENG
- CECS 593 - IND STUDY IN CECS
- CECS 693 - INDEP STUDY CECS
- CECS 694 - SP TOP-CECS
- CECS 696 - CECS PROJECT
Summer
- CECS 694 - SP TOP-CECS
- CECS 696 - CECS PROJECT
- CECS 568 - COMPUTER FORENSICS
- CECS 690 - MS THESIS COMP SCI
- CECS 697 - MENG THESIS IN CECS
- CECS 696 - CECS PROJECT
- CECS 568 - COMPUTER FORENSICS
- CECS 596 - CECS CAPSTONE DESIGN - CUE
Fall
- CECS 795 - SEM IN COMPUTER & ENG
2018
Fall
- CECS 795 - SEM IN COMPUTER & ENG
- CECS 694 - SP TOP-CECS
- CECS 696 - CECS PROJECT
- CECS 799 - DISSERTATION RESEARCH
- CECS 795 - SEM IN COMPUTER & ENG
- CECS 693 - INDEP STUDY CECS
- CECS 696 - CECS PROJECT
Spring
- CECS 690 - MS THESIS COMP SCI
- CECS 696 - CECS PROJECT
- CSE 693 - DISSERTATION RESEARCH
- CSE 695 - SEMINAR IN CSE
- CECS 690 - MS THESIS COMP SCI
- CECS 696 - CECS PROJECT
Summer
- CECS 393 - IND STUDY IN CECS
- CECS 696 - CECS PROJECT
- CECS 568 - COMPUTER FORENSICS
- CECS 799 - DISSERTATION RESEARCH
- CECS 690 - MS THESIS COMP SCI
- CECS 696 - CECS PROJECT
- CECS 568 - COMPUTER FORENSICS
- CECS 596 - CECS CAPSTONE DESIGN - CUE
2017
Fall
- CECS 693 - INDEP STUDY CECS
- CECS 696 - CECS PROJECT
- CSE 693 - DISSERTATION RESEARCH
- CSE 695 - SEMINAR IN CSE
- CECS 593 - IND STUDY IN CECS
- CECS 696 - CECS PROJECT
Spring
- CECS 696 - CECS PROJECT
- CSE 693 - DISSERTATION RESEARCH
- CSE 695 - SEMINAR IN CSE
- CECS 690 - MS THESIS COMP SCI
- CECS 602 - GRAD INTERNSHIP IN CECS
- CECS 696 - CECS PROJECT
Summer
- CECS 696 - CECS PROJECT
- CSE 693 - DISSERTATION RESEARCH
- CECS 690 - MS THESIS COMP SCI
- CECS 602 - GRAD INTERNSHIP IN CECS
- CECS 696 - CECS PROJECT
- CECS 596 - CECS CAPSTONE DESIGN - CUE
2016
Spring
- CECS 696 - CECS PROJECT
- CSE 693 - DISSERTATION RESEARCH
- CSE 695 - SEMINAR IN CSE
- CECS 690 - MS THESIS COMP SCI
- CECS 696 - CECS PROJECT
- CECS 596 - CECS CAPSTONE DESIGN - CUE
Fall
- CECS 696 - CECS PROJECT
- CSE 693 - DISSERTATION RESEARCH
- CSE 695 - SEMINAR IN CSE
- CECS 593 - IND STUDY IN CECS
- CECS 697 - MENG THESIS IN CECS
- CECS 602 - GRAD INTERNSHIP IN CECS
- CECS 696 - CECS PROJECT
Summer
- CECS 696 - CECS PROJECT
- CSE 693 - DISSERTATION RESEARCH
- CECS 697 - MENG THESIS IN CECS
- CECS 696 - CECS PROJECT
2015
Spring
- CECS 696 - CECS PROJECT
- CSE 693 - DISSERTATION RESEARCH
- CSE 695 - SEMINAR IN CSE
- CECS 393 - IND STUDY IN CECS
- CECS 593 - IND STUDY IN CECS
- CECS 593 - IND STUDY IN CECS
- CECS 690 - MS THESIS COMP SCI
- CECS 693 - INDEP STUDY CECS
- CECS 696 - CECS PROJECT
- CECS 596 - CECS CAPSTONE DESIGN;CUE
Fall
- CECS 696 - CECS PROJECT
- CECS 596 - CECS CAPSTONE DESIGN - CUE
- CSE 693 - DISSERTATION RESEARCH
- CSE 695 - SEMINAR IN CSE
- CECS 602 - GRAD INTERNSHIP IN CECS
- CECS 696 - CECS PROJECT
Summer
- CECS 696 - CECS PROJECT
- CSE 693 - DISSERTATION RESEARCH
- CECS 593 - IND STUDY IN CECS
- CECS 690 - MS THESIS COMP SCI
- CECS 696 - CECS PROJECT
2014
Fall
- CECS 696 - CECS PROJECT
- CECS 568 - COMPUTER FORENSICS
- CECS 596 - CECS CAPSTONE DESIGN;CUE
- CSE 693 - DISSERTATION RESEARCH
- CSE 695 - SEMINAR IN CSE
- CECS 393 - IND STUDY IN CECS
- CECS 602 - GRAD INTERNSHIP IN CECS
- CECS 696 - CECS PROJECT
Summer
- CECS 696 - CECS PROJECT
- CSE 693 - DISSERTATION RESEARCH
- CECS 393 - IND STUDY IN CECS
- CECS 593 - IND STUDY IN CECS
- CECS 696 - CECS PROJECT
Spring
- CSE 693 - DISSERTATION RESEARCH
- CSE 695 - SEMINAR IN CSE
- CECS 690 - MS THESIS COMP SCI
- CECS 697 - MENG THESIS IN CECS
- CECS 696 - CECS PROJECT
- CECS 596 - CECS CAPSTONE DESIGN;CUE
2013
Fall
- CECS 696 - CECS PROJECT
- CECS 596 - CECS CAPSTONE DESIGN;CUE
- CECS 568 - COMPUTER FORENSICS
- CSE 693 - DISSERTATION RESEARCH
- CSE 695 - SEMINAR IN CSE
- CECS 593 - IND STUDY IN CECS
- CECS 696 - CECS PROJECT
Summer
- CSE 693 - DISSERTATION RESEARCH
- CECS 690 - MS THESIS COMP SCI
- CECS 697 - MENG THESIS IN CECS
- CECS 696 - CECS PROJECT

Adel Elmaghraby

Education

Publications

Additional Publications

More about Adel Elmaghraby

Awards and Recognition

Courses Taught