Omar Soufi | Intelligence Artificial | Best Researcher Award

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Dr. Omar Soufi | Intelligence Artificial | Best Researcher Award

Doctorate at Mohammed V University of Rabat Mohammadia School of Engineering, Morocco

Summary:

Dr. Omar Soufi is an expert in artificial intelligence and data science, with a specialized focus on remote sensing and geographic information systems (GIS). He completed his Ph.D. in Computer Engineering with a concentration in Artificial Intelligence at EMI Rabat in 2023, where his research centered on enhancing satellite image quality using deep learning techniques. With extensive experience in both academia and industry, Dr. Soufi has led numerous projects in AI, data science, and business intelligence. His contributions to the field include developing geospatial platforms for natural disaster risk management and implementing innovative solutions for satellite image processing. Dr. Soufi is currently advancing his research and professional endeavors as a postdoctoral researcher at CRTS Rabat, where he continues to explore the frontiers of AI and remote sensing.

Professional Profile:

👩‍🎓Education:

  • Ph.D. in Computer Engineering: Artificial Intelligence (2023)
    • Institution: EMI Rabat
    • Dissertation: Approche par Deep Learning au profit de la télédétection spatiale : Amélioration de la qualité d’images satellites et du procédé du capteur d’étoile.
  • Engineering Degree in Computer Science (2020)
    • Institution: EMI Rabat
    • Option: Ingénierie et Qualité Logicielle.
  • Engineering Degree in Information Systems Engineering (2020)
    • Institution: Polytechnique Grenoble, ENSIMAG
  • Fundamental License in Mechanical Engineering (2014)
    • Institution: ARM Merkèns
  • Diplôme des Études Universitaires (2015)
    • Institution: ARM Merkèns
  • Baccalauréat (2011)
    • Institution: 1ER LMR
    • Option: Sciences de Vie et de Terre

🏢 Professional Experience:

Dr. Omar Soufi is currently a Postdoctoral Researcher in Computer Engineering at CRTS Rabat, a position he has held since February 2024. In this role, he leads projects focused on artificial intelligence and data science, particularly for satellite image processing and spatial data analysis. Since 2022, Dr. Soufi has also been the Head of the Geomatics & Decision-Making Tools Department at CRTS Rabat, where he manages geomatics projects, develops decision-making tools, and oversees the implementation of geospatial platforms.

Previously, from 2020 to 2022, Dr. Soufi served as the Head of the Business Intelligence & Decision-Making Tools Department at CRTS Rabat. In this capacity, he directed business intelligence projects, developed data analytics solutions, and optimized decision-making processes. From 2017 to 2020, he was the Chief of Project at the Decision Support Center, managing decision support projects, implementing big data architectures, and developing e-learning platforms.

Dr. Soufi’s earlier professional experience includes serving as a Project Manager in the IT Department at CRTS Rabat from 2016 to 2017. He led IT projects, developed web applications, and implemented distributed data processing systems. His internships include a PFE internship on the super resolution of satellite images using deep learning (February 2020 – July 2020), an engineering internship on the development of a space station management platform at CRERS Rabat (July 2019 – August 2019), and an internship on the development of an agricultural campaign bulletin diffusion platform at CRTS Rabat (July 2019 – August 2019).

Research Interests

Dr. Omar Soufi’s research interests are centered on artificial intelligence, data science, remote sensing, and geographic information systems (GIS). His work focuses on applying deep learning techniques to improve the quality of satellite images and developing intelligent systems for spatial data analysis and geospatial applications. He is particularly interested in enhancing accessibility to high-resolution satellite imagery and advancing spacecraft attitude control using AI.

Top Noted Publication:

  • Study of Deep Learning-Based Models for Single Image Super-Resolution
    • Authors: O. Soufi, F.Z. Belouadha
    • Published in: Revue d’Intelligence Artificielle, 2022
    • Link: DOI: 10.18280/ria.360616
  • FSRSI: New Deep Learning-Based Approach for Super-Resolution of Multispectral Satellite Images
  • Deep Learning Technique for Image Satellite Processing
    • Authors: O. Soufi, F.Z. Belouadha
    • Published in: Intell Methods Eng Sci, 2023
  • Enhancing Accessibility to High-Resolution Satellite Imagery: A Novel Deep Learning-Based Super-Resolution Approach
    • Authors: O. Soufi, F.Z. Belouadha
    • Published in: Journal of Environmental Treatment Techniques, 2023
  • An Intelligent Deep Learning Approach to Spacecraft Attitude Control: The Case of Satellites
    • Authors: O. Soufi, F.Z. Belouadha
    • Status: Under review, 2023

Wadha Abdullah Al-Khater | Computer Science | Best Researcher Award

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Dr. Wadha Abdullah Al-Khater, Computer Science, Best Researcher Award

Doctorate at Qatar University, Saudi Arabia

Summary:

Dr. Wadha Abdullah Al-Khater is a prominent researcher in the field of cybersecurity. She has contributed significantly to the development of malware detection techniques using deep learning models and innovative methodologies. With expertise in cybercrime detection and radio frequency identification methods, Dr. Al-Khater has published several articles and conference papers that have garnered considerable attention in the academic community. Her work has been recognized for its comprehensive review of cybercrime detection techniques, providing valuable insights into addressing contemporary challenges in cybersecurity.

Professional Profile:

Scopus Profile

👩‍🎓Education & Qualification:

PhD in Cyber Security (In Progress)

  • Qatar University
  • Start Date: January 29, 2024

Master’s Degree in Computer Science

  • King Saud University
  • Graduation Date: February 25, 2014
  • GPA: 4.62

Bachelor’s Degree in Computer Science

  • College of Education for Girls at Jubail City, King Faisal University
  • Graduation Date: July 2006
  • Honors: Excellent with Honors

Professional Experience:         

Dr. Wadha Abdullah Al-Khater has amassed a rich academic background with diverse roles across various institutions:

Lecturer at CCQ

  • Duration: August 30, 2016 – Present

Graduate Assistantship at Qatar University

  • Duration: March 31, 2016 – August 31, 2016

Lecturer at University Of Dammam

  • Duration: Since October 2008 (corresponding to 1429 H in the Hijri calendar) until present

Teaching Assistant at University Of Dammam

  • Duration: August 16, 2006 (corresponding to 8/1427 H) – June 13, 2008 (corresponding to 6/1429 H in the Hijri calendar)

IT Instructor

  • Conducted a summer course in the Prince Mohammad Bin Fahd Bin Abdul-Aziz Al Sa’ud program aimed at qualifying and employing Saudi youth from May 21, 2007 to July 1, 2007 (corresponding to 21/5/1427 H – 1/7/1427 H).
  • Taught ICDL Certification at Eqra school in Jubail in 1427 H.
  • Compiled a one-month course at University Of Dammam on combining database with Visual Basic in 1430 H.
  • Compiled courses at University Of Dammam in Photoshop and Successful Strategies for Students Studying aimed at preparatory year students.

Honors and awards:

Dr. Wadha Abdullah Al-Khater’s academic excellence was recognized with First Class Honors in the B.Sc. Program at the College of Education for Girls in Jubail City, which is affiliated with King Faisal University. This achievement underscores her dedication and exceptional performance in her academic pursuits.

 Research Interest:

Publication Top Noted:

Using 3D-VGG-16 and 3D-Resnet-18 deep learning models and FABEMD techniques in the detection of malware

  • Authors: W. Al-Khater, S. Al-Madeed
  • Journal: Alexandria Engineering Journal
  • Year: 2024
  • Volume: 89
  • Pages: 39–52

Comprehensive review of cybercrime detection techniques

  • Authors: W.A. Al-Khater, S. Al-Maadeed, A.A. Ahmed, A.S. Sadiq, M.K. Khan
  • Journal: IEEE Access
  • Year: 2020
  • Volume: 8
  • Pages: 137293–137311
  • Paper ID: 9146148
  • Citation count: 54

A review on Radio Frequency Identification methods

  • Authors: W. Al-Khater, S. Kunhoth, S. Al-Maadeed
  • Conference: 2017 13th International Wireless Communications and Mobile Computing Conference, IWCMC 2017
  • Year: 2017
  • Pages: 1751–1758
  • Paper ID: 7986549
  • Citation count: 5