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

Pablo Arnau González | Artificial Intelligence | Best Researcher Award

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Dr. Pablo Arnau González, Artificial Intelligence, Best Researcher Award

Doctorate at Universidad de Valencia, Spain

Summary:

Dr. Pablo Arnau González is a researcher with expertise in artificial intelligence and machine learning. He has made significant contributions to the fields of sentiment analysis, affective computing, and biometrics. Dr. González has conducted research on adapting conversational toolkits for sentiment analysis tasks and developing methodologies for identifying affect levels from EEG signals and visual stimuli. He has also contributed to the development of adaptive intelligent tutoring systems. With a background in computing and artificial intelligence, Dr. González has published several papers in reputable conferences and journals.

Professional Profile:

Scopus Profile

Orcid Profile

Google Scholar Profile

👩‍🎓Education & Qualification:

PhD in Computing and Artificial Intelligence

  • University of the West of Scotland, 2020

Graduado o Graduada en Ingeniería Informática de Gestión y Sistemas de Información

  • Universitat de València, 2015

Professional Experience:

Dr. Pablo Arnau González has a diverse professional background, including positions in consulting, industry, and academia. Here is a summary of his previous professional positions:

  • 2022 – 2023: Postdoctoral Fellow (Margarita Salas) at Universitat de València.
  • 2021: Senior Consultant at SDG Consulting.
  • 2019 – 2021: Analyst at Cecotec Innovaciones, S.L.
  • 2019: Technologist in Digital Health at the University of the West of Scotland.

Research Interest:

Artificial Intelligence: Exploring AI algorithms and techniques for various applications such as sentiment analysis, affective computing, and intelligent tutoring systems.

Machine Learning: Investigating machine learning models and methodologies for processing EEG signals and visual stimuli to identify affect levels and subject identification.

Natural Language Processing: Adapting conversational toolkits and architectures for tasks like sentiment analysis, chatbots, and conversational agents.

Biometrics: Researching the use of EEG signals and image-evoked affect for biometric authentication and identification systems.

Adaptive Intelligent Tutoring Systems: Developing systems that can assess affective and behavioral responses to adaptively tailor educational content and interactions.

Publication Top Noted:

On adapting the DIET architecture and the Rasa conversational toolkit for the sentiment analysis task

  • Authors: M Arevalillo-Herráez, P Arnau-González, N Ramzan
  • Journal: IEEE Access
  • Year: 2022
  • Volume: 10
  • Pages: 107477-107487
  • Citation count: 11

A Method to Identify Affect Levels from EEG signals using two-dimensional Emotional Models

  • Authors: P Arnau-González, N Ramzan, M Arevalillo-Herráez
  • Conference: The 2016 European Simulation and Modelling Conference
  • Year: 2016
  • Pages: 299-303
  • Citation count: 8

Image-evoked affect and its impact on EEG-based biometrics

  • Authors: P Arnau-González, S Katsigiannis, M Arevalillo-Herráez, N Ramzan
  • Conference: 26th IEEE International Conference on Image Processing
  • Year: 2019
  • Citation count: 7

Single-channel EEG-based subject identification using visual stimuli

  • Authors: S Katsigiannis, P Arnau-González, M Arevalillo-Herráez, N Ramzan
  • Conference: 2021 IEEE EMBS International Conference on Biomedical and Health Informatics
  • Year: 2021
  • Citation count: 5

Affective and Behavioral Assessment for Adaptive Intelligent Tutoring Systems

  • Authors: L Marco-Giménez, M Arevalillo-Herráez, FJ Ferri, S Moreno-Picot, …
  • Conference: UMAP (Extended Proceedings)
  • Year: 2016
  • Citation count: 5