E-JUST Academic profiles

Personal Info

Academic profile overview

Address

Mobile

Office

Department

Computer Science & Engineering

Biography

Rami Zewail, PhD, PEng

PhD in Electrical & Computer Engineering, University of Alberta

20+ Academic & Industrial R&D Experience, Resource-Aware AI, Intelligent Systems & Computer Vision Expert.

Over 20 years of academic and industrial R&D experience spanning the Oil & Gas, Healthcare, and Industrial sectors. Proven track record in developing autonomous systems and real-time edge analytics deployed in harsh environments. My expertise lies at the intersection of Embedded Systems, Artificial Intelligence, and Computer Vision, with a specialized R&D focus on resource-aware AI and embedded intelligence (Edge AI)—driving innovation across various domains from next-gen healthcare diagnostics to Industry 4.0.

You can explore my full portfolio—including my research focus, publications, industrial R&D innovations, and teaching experience—here: https://sites.google.com/ejust.edu.eg/rami-zewail/

Research Interests

I am currently affiliated with the Computer Science & Engineering Department at Egypt-Japan University of Science & Technology, where I am actively involved in research initiatives in Resource-Aware AI, computer vision, and embedded intelligence.

Research Focus - Resource-Aware Intelligence

My research framework focuses on the synergy between algorithmic efficiency and hardware implementation to address the challenges of intelligent systems in harsh, resource-constrained environments. I specialize in developing robust solutions for learning from limited and noisy data, operating under intermittent power or connectivity conditions, and optimizing AI models for deployment on platforms with strictly limited compute, memory, and energy budgets.

Sustainable Development GoalsAreas of academic contribution aligned with the UN SDGs

Awards

Honors & achievements

Honors & Awards

Technical Award: National Oilwell Varco (2014) for “Downhole Downlink Communication System”.
Technical Award: National Oilwell Varco (2014) for “Rotary Steerable Tool”.
Technical Award: National Oilwell Varco (2014) for “Electronically Actuated Under-Reamer”.
Izaak Walton Killam Memorial Scholarship: University of Alberta, 2007.
Invited AI Expert: 3rd GPAI Tokyo Innovation Workshop, 2025.

Professional Service & Membership

Member: MENA Observatory on Responsible AI, AUC.
Judge: Responsible AI Cup, AUC (2025).
Organizer: AI-Accelerated Appathon, E-JUST (2025).
Host/Organizer: UNESCO Regional Education Advisor visit to EJUST (2026).
Invited Academic AI Expert: UNESCO National Validation Workshop (2025).
Invited Speaker: Global Petroleum Show, Calgary (2019).
Professional Member (P.Eng.): APEGA (2004–2020).
Conference Host Speaker: JAC-ECC (2024, 2025).
Session Chair: JAC-ECC (2021–2025).
Member: Canadian Artificial Intelligence Association (2017–2020).
Member: Egyptian Engineering Syndicate (2002–Present).

Impacted Journal

Journal publications

Journal Articles

Z. Selim, M. Hamed, W. Ahmed, S. Said, S. Basheer, and R. Zewail, "Edge-Native Multimodal RAG: Hardware-Aware Quantization and Architectural Optimization for Consumer GPUs," Journal of Systems Architecture, Elsevier (Under Review, 2026).
R. Zewail, B. Mokhtar, "Contrastive Scattering Meta-Learning Framework for Online few-shot Acoustic Anomaly Detection," Journal of Advanced Intelligent Systems, Wiley (Accepted, 2026).
R. Zewail, "When and How to Focus: A Task-Dependent Analysis of Efficient Attentive Architectures for Biosignal Classification," IEEE Access, Feb, Jan. 2026.
R. Zewail, "Manifold-Aware Diffusion-Augmented Contrastive Learning for Noise-Robust Biosignal Representation," International Journal of Online and Biomedical Engineering (iJOE), April, 2026.
I. Schuler, M. Schuler, T. Frick, D. Jimenez, A. Maghnouj, S. Hahn, R. Zewail, K. Gerwert, and S. F. ElMashtoly, "Efficacy of tyrosine kinase inhibitors examined by a combination of Raman micro-spectroscopy and a deep wavelet scattering-based multivariate analysis framework," The Analyst, 2024.
O. Mogaka, R. Zewail, K. Inoue, M. S. Sayed, "Tiny EmergencyNet: A hardware-friendly ultra-lightweight deep learning model for aerial image scene classification," Journal of Real-Time Image Processing, Springer, 2024.
D. Aboutahoun, R. Zewail, K. Kimura, and M. I. Soliman, "Lightweight Histological Tumor Classification using a Joint Sparsity-Quantization Aware Training Framework," IEEE Access, doi: 10.1109/ACCESS.2023.3327221, 2023.
Z. Alkayem, R. Zewail, A. Shoukry, D. Kawahara, and S. A. Elsagheer Mohamed, "A Novel Global Prototype-Based Node Embedding Technique," IEEE Access, vol. 10, pp. 125311-125318, 2022.
R. Zewail, A. Hag-ElSafi, "Appearance-based Salient Features Extraction in Medical Images Using Sparse Contourlet-based Representation," International Journal of Image, Graphics and Signal Processing, vol. 9, no. 9, 2017.
R. Zewail, A. Hag-ElSafi, "Multi-scale Sparse Appearance Modeling And Simulation of Pathological Deformations," ICTACT Journal on Image and Video Processing, 2017.

International Conference

International academic activity

Conference Proceedings

A. Elkolally, A. Dorgham, A. Etman, R. Zewail, K. Inoue, and M. Sayed, "A Unified Reinforcement Learning Framework for Energy-Harvesting Vision Systems," 9th IFIP International Internet of Things (IoT) Conference, UAE, 2026 (Under Review).
M. A. Farag, H. A. Suleiman, R. Zewail, A. Nassrallah, A. Abdel-Mawgood, S. A. Awad, B. Anis, and S. F. El-Mashtoly, "Continual Learning Strategies for Sequential Pathogen Update in Raman Spectroscopy-Based Identification," 29th International Conference on Raman Spectroscopy, Turkey, 2026 (Accepted).
O. AbdElkarim, R. Zewail, K. Inoue, S. Sherif, M. ElSayed, "FPGA-Based Artificial Intelligence Accelerator for on-Board Processing of Aerial Scenes," IEEE International Conference on Microelectronics (IEEE-ICM), Dec. 2025.
R. Zewail, "Scattering Transformer: A Training-Free Transformer Architecture for Heart Murmur Detection," MEDI 2025, Lecture Notes in Computer Science (accepted). arXiv:2509.18424.
O. Mahmoud, K. Gad, S. Zeineldeen, M. Moawad, Y. Masoud, E. Osama, R. Zewail, M. Sayed, "A Verification and Performance Evaluation Framework for RISC-V Vector Kernels," 13th International Japan-Africa Conference on Electronics, Communications and Computations (JAC-ECC), 2025.
D. Aboutahoun, R. Zewail, K. Kimura, and M. I. Soliman, "Cross-Domain Few-Shot Sparse Quantization Aware Learning for Lymphoblast Detection in Blood Smear Images," Pattern Recognition, Lecture Notes in Computer Science, Springer Nature, pp. 213-226, 2023.
J. Herman, R. Zewail, T. Ogawa, and S. ElSagheer, "A Lightweight Transfer Learning Based Model for Building Classification in Aerial Imagery," 15th International Conference on Computer Research and Development (ICCRD), IEEE, pp. 181-186, 2023.
E. Mansour, M. Shahin, A. Ashraf, A. Atta, A. Allam, R. Zewail, "Review on Non-Invasive Electromagnetic Approaches for Blood Glucose Monitoring Using Machine Learning," JAC-ECC, 2023.
A. Hassan, A. Yahia, M. Tamer, M. Shahin, R. Zewail, O. Abdel-Rahim, "Advances in Lithium-Ion Battery SOC Prediction: A Data-Driven GRU-RNN Framework," JAC-ECC, 2023.
D. Aboutahoun, R. Zewail, M. I. Soliman, "On Potentials of Few-Shot Learning for AI-Enabled Internet of Medical Things," IEEE Globecom Workshops, Rio de Janeiro, pp. 10621067, 2022.
R. Zewail, T. Bakr, A. Abdullatif, "Resource-Aware Identification Of COVID-19 Cough Sounds Using Wavelet Scattering Embeddings," 2nd International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC), Cairo, 2022.
T. Bakr, A. Abdullatif, K. Elzeky, M. ElSayed, R. Zewail, "Cross-Lingual Transfer Learning for Arabic Signature Verification: Dataset and Baseline Evaluation," 6th International Conference on Imaging, Vision & Pattern Recognition (IVPR).
R. Zewail, A. Elsafi, N. Durdle, "Vertebral Shape Analysis using Multi-scale Shape Parameters and Statistical Regression," Research into Spinal Deformities 7 (Studies in Health Technology and Informatics), 2010.
R. Zewail, A. Elsafi, N. Durdle, "Vertebral segmentation using contourlet-based salient point matching and localized multiscale shape prior," Medical Imaging 2009: Image Processing, SPIE, 2009.
A. Elsafi, R. Zewail, N. Durdle, "Steerable optical flow based image registration: application to aligning human torso images," Visual Information Processing XVIII, 2009.
R. Zewail, A. Elsafi, N. Durdle, "Quantification of Localized Vertebral Deformities Using a Sparse Wavelet-based Shape Model," Research into Spinal Deformities 6 (Studies in Health Technology and Informatics), 2008.
R. Zewail, A. Elsafi, N. Durdle, "Vertebral classification using localized pathology-related shape model," Medical Imaging 2008: Image Processing, SPIE, 2008.
A. Elsafi, R. Zewail, N. Durdle, "Statistical simulation of deformations using wavelet independent component analysis," Visual Information Processing XVII, 2008.
R. Zewail, A. Elsafi, N. Durdle, "Wavelet-based independent component analysis for statistical shape modeling," Canadian Conference on Electrical and Computer Engineering (CCECE), 2007.
A. Elsafi, R. Zewail, N. Durdle, "Statistical deformation model for intensity based image registration," Canadian Conference on Electrical and Computer Engineering (CCECE), 2007.
R. Zewail, A. Elsafi, N. Durdle, "Multi-scale shape prior using wavelet packet representation and independent component analysis," Medical Imaging 2007: Image Processing, SPIE, 2007.
A. Elsafi, R. Zewail, N. Durdle, "Elastic image registration using subspace constraints," Visual Information Processing XVI, 2007.
R. Zewail, A. Elsafi, M. Saeb, N. Hamdy, "Soft and hard biometrics fusion for improved identity verification," 47th Midwest Symposium on Circuits and Systems (MWSCAS), 2004.
R. Zewail, A. Seif, M. Saeb, N. Hamdy, "Fingerprint recognition based on spectral feature extraction," 46th Midwest Symposium on Circuits and Systems (MWSCAS), 2003.
A. Seif, R. Zewail, M. Saeb, N. Hamdy. "Iris identification based on log Gabor filtering," 46th Midwest Symposium on Circuits and Systems (MWSCAS), 2003.

Book Chapters

R. Zewail, "Multimodal Diagnosis of COVID-19 Using Deep Wavelet Scattering Networks," in Advanced AI and Internet of Health Things for Combating Pandemics, Springer Internet of Things Book Series, June 2023.

Tutorials

A. Hag ElSafi and R. Zewail, "AI-STREAM Digital Transformation Challenge Event: The BIG Data vs Sparse Data Challenge," IEEE Virtual World Forum on Internet of Things (WF-IoT), Tutorial TUT-04, August 2020.

Funded Research Grants

Research funding & projects

Active Grants

ITIDA (2024-2026): Embedded AI-Enabled Acoustic-Aware Anomaly Detection EDGE Device.
STDF (2025-ongoing): Development of a label-free new technology based on Raman spectroscopy and artificial intelligence for food safety.

Industrial R&D Projects

Alberta Innovates, Alberta, Canada (2018): Prototyping Artificial Intelligence Enabled Tags for Industry 4.0 Applications.
National Oilwell Varco, Alberta, Canada (2010-2017): Development of intelligent autonomous directional drilling technologies.
Smart Empower Innovation Labs Inc., Alberta, Canada (2017-2020): R&D of autonomous intelligent systems, downhole data logging tools, and data visualization/analytics for pipeline inspection.
National Oilwell Varco, Alberta, Canada (2007-2017): R&D for real-time EDGE analytics, digital twins, stick-slip mitigation, and condition monitoring algorithms for harsh environments.

PhD Research

During my PhD at University of Alberta, Canada, I conducted research on artificial intelligence for medical image analysis and computer-aided diagnosis.

Courses Teaching

Teaching & academic courses

My pedagogical approach centers on project-based learning, designed to bridge the gap between abstract academic theory and the practical constraints of industrial application. By integrating my research in resource-aware intelligence directly into the classroom, I challenge students to solve real-world engineering problems, ensuring they graduate with the technical depth and professional mindset required to navigate the complexities of modern industry

Postgraduate (PG) Courses

CSE 521: Embedded Machine Learning
CSE 624: Resource-Aware Machine Learning
CSE 501: Advanced Programming Concepts
CSE 505: Advanced Embedded Systems
PRE 421: Analysis of Algorithms

Undergraduate (UG) Courses

CSE 324: Embedded Systems
CSE 436: Advanced Embedded Systems
CSE 211: Computer Programming
CSE 313: Advanced Computer Programming
CSE 322: Software Engineering
CSE 431: Advanced Computer Architecture
CSE 321: Project-Based Learning
CSE 420/500: Graduation Projects I & II