Yousri Kessentini | Artificial Intelligence | Best Researcher Award

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Assoc. Prof. Dr. Yousri Kessentini | Artificial Intelligence | Best Researcher Award

Senior Researcher at Digital research center of Sfax, Tunisia

Assoc. Prof. Dr. Yousri Kessentini is a computer science researcher and Associate Professor at the Digital Research Center of Sfax, Tunisia, where he leads the DeepVision research team. He holds a Ph.D. from the University of Rouen, France, and specializes in deep learning, computer vision, and document image analysis. Dr. Kessentini has coordinated numerous national and international research projects and has received several awards, including honors from NVIDIA and the National Academy of Engineering. He is a certified Deep Learning instructor and an active contributor to the scientific community through publications, supervision, and editorial roles.

Publication Profile 

Scopus

Orcid

Educational Background 

Dr. Kessentini earned his Habilitation in Computer Science from the University of Sfax in 2021. He holds a Ph.D. in Computer Science (2006–2009) and a DEA (postgraduate diploma) in Computer Science (2004) from the University of Rouen, France. He also obtained an engineering diploma in computer science from ENIS in 2003 and completed his secondary education with a Scientific Baccalaureate in Mathematics in 1998.

Professional Experience

Dr. Kessentini has accumulated rich academic and industrial experience over two decades. Since 2022, he has served as Associate Professor and Head of the DeepVision research team at CRNS. From 2017 to 2021, he was a senior researcher at the same center. Between 2013 and 2017, he was an assistant professor at ISIMA University of Monastir. He also held postdoctoral and graduate assistant roles in France, including at ITESOFT/LITIS and the University of Rouen. Since 2018, he has been a certified instructor and ambassador of the NVIDIA Deep Learning Institute, reflecting his leadership in AI education and training.

Research Interests

His research spans a variety of deep learning applications, including document image recognition, handwritten text analysis, multi-script OCR, generative models, and satellite image fusion. Dr. Kessentini also explores the intersection of AI with healthcare, smart cities, and industrial automation. His recent projects involve federated learning for medical imaging, vehicle identity recognition, Arabic script analysis, and human action recognition through remote sensing and video surveillance.

Awards and Honors

Dr. Kessentini has received numerous accolades for his contributions to AI research and innovation. In 2025, he was selected for the prestigious U.S.-Africa Frontiers of Science, Engineering, and Medicine Symposium by the U.S. National Academy of Engineering. He ranked first in Tunisia’s national recruitment competition for associate professors in 2022. He received best student paper awards at ICPR 2020 and MedPRAI 2020 and earned a Jury Recognition Award in Tunisia’s national innovation competition in 2019. His research excellence was also recognized by NVIDIA with a GPU Grant in 2018, the same year he was certified as an official instructor and ambassador.

Publications 

Title: Information extraction from multi-layout invoice images using FATURA dataset

Year: 2025

Title: STF-Trans: A Two-stream SpatioTemporal Fusion Transformer for Very High Resolution Satellites Images

Year: 2024

Title: MSdocTr-Lite: A Lite Transformer for Full Page Multi-script Handwriting Recognition

Year: 2023

Title: Spectral-Temporal Fusion of Satellite Images Via an End-to-End Two-Stream Attention With an Effective Reconstruction Network

Year: 2023

Title: Few Shots Are All You Need: A Progressive Few Shot Learning Approach for Low Resource Handwriting Recognition

Year: 2022

Conclusions

Assoc. Prof. Dr. Yousri Kessentini stands out as a leading figure in the fields of artificial intelligence and computer vision. His consistent contributions to scientific innovation, mentorship, and international collaboration have had a significant impact across academia and industry. His work demonstrates not only technical excellence but also a strong commitment to applying AI for societal and industrial benefit. With an impressive track record of publications, project leadership, and academic service, he is highly deserving of recognition in competitive research and innovation awards.

Muhammad Kashif Jabbar | Artificial Intelligence | Best Researcher Award

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Mr. Muhammad Kashif Jabbar | Artificial Intelligence | Best Researcher Award

Doctor Student at Shenzhen University, China

Muhammad Kashif Jabbar is a research-focused professional specializing in medical image processing. With a strong foundation in Electronics and Information Engineering, he has contributed significantly to research, particularly in developing transfer learning-based models for diabetic retinopathy diagnosis. Muhammad Kashif is multilingual, skilled in technical domains, and experienced in international collaborations.

Publication Profile 

Scopus

Educational Background 🎓

  1. Shenzhen University
    • Degree: Ph.D. in Electronics and Information Engineering
    • Specialization: Medical Image Processing
    • Session: September 2018 – June 2022
  2. Beijing University of Technology (BJUT)
    • Degree: Master’s in Information and Communication Engineering
    • Specialization: Medical Image Processing
    • Session: September 2018 – June 2022
  3. Superior University of Lahore
    • Degree: Master’s in Information Technology (MIT)
    • Session: 2014 – 2016

Professional Experience 💼

  • Worked extensively on developing advanced methodologies in medical image processing.
  • Conducted research focusing on diabetic retinopathy diagnosis, utilizing transfer learning techniques.
  • Developed applications in web development and database management.

Research Interests 🔬

  • Medical Image Processing
  • Transfer Learning for Disease Diagnosis
  • Data Security in Medical Imaging (Steganography and Cryptography)
  • Artificial Intelligence and Optimization Algorithms in Healthcare Applications

Awards and Honors🏆✨

  • Passed HSK4 Chinese Language Proficiency Exam (2018).
  • Performed at the 14th BJUT International Day opening ceremony.
  • Recognized for successful completion of the 2019 International Students Exploring Haidian program.

Certifications

  1. HSK4 Chinese Language Certification – Beijing University of Technology
  2. Graphic Design – ARENA Multimedia, Islamabad Campus (2015)

Conclusion🌟

Muhammad Kashif Jabbar is a highly skilled researcher with a passion for advancing medical technologies using artificial intelligence and image processing techniques. His education and expertise make him a valuable asset to organizations focused on cutting-edge medical research and innovation.

Publications 📚

📡 Radar and Engineering

  1. Enhancing Radar Tracking Accuracy Using Combined Hilbert Transform and Proximal Gradient Methods
    • Authors: Jabbar, A., Jabbar, M.K., Jabbar, A., Mahmood, T., Rehman, A.
    • Journal: Results in Engineering, 2024, 24, 103479.
    • 🌐 Type: Article (Open Access)
    • 📊 Citations: 0

👁️ Ophthalmology and AI

  1. A Retinal Detachment Based Strabismus Detection Through FEDCNN
    • Authors: Jabbar, A., Jabbar, M.K., Mahmood, T., Nobanee, H., Rehman, A.
    • Journal: Scientific Reports, 2024, 14(1), 23255.
    • 🌐 Type: Article (Open Access)
    • 📊 Citations: 0

🔄 Errata and Corrections

  1. Correction to: Deep Transfer Learning-Based Automated Diabetic Retinopathy Detection Using Retinal Fundus Images in Remote Areas
    • Authors: Jabbar, A., Naseem, S., Li, J., Rehman, A., Saba, T.
    • Journal: International Journal of Computational Intelligence Systems, 2024, 17(1), 145.
    • 🌐 Type: Erratum (Open Access)
    • 📊 Citations: 1

  2. Correction to: Transfer Learning-Based Model for Diabetic Retinopathy Diagnosis Using Retinal Images

    • Authors: Jabbar, M.K., Yan, J., Xu, H., Ur Rehman, Z., Jabbar, A.
    • Journal: Brain Sciences, 2024, 14(8), 777.
    • 🌐 Type: Erratum (Open Access)
    • 📊 Citations: 0

🧠 Diabetic Retinopathy and AI Models

  1. Transfer Learning-Based Model for Diabetic Retinopathy Diagnosis Using Retinal Images
    • Authors: Jabbar, M.K., Yan, J., Xu, H., Rehman, Z.U., Jabbar, A.
    • Journal: Brain Sciences, 2022, 12(5), 535.
    • 🌐 Type: Article (Open Access)
    • 📊 Citations: 49