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
Educational Background π
- Shenzhen University
- Degree: Ph.D. in Electronics and Information Engineering
- Specialization: Medical Image Processing
- Session: September 2018 β June 2022
- Beijing University of Technology (BJUT)
- Degree: Masterβs in Information and Communication Engineering
- Specialization: Medical Image Processing
- Session: September 2018 β June 2022
- Superior University of Lahore
- Degree: Masterβs in Information Technology (MIT)
- Session: 2014 β 2016
Professional Experience πΌ
- 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 π¬
- 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 Honorsπβ¨
- 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
- HSK4 Chinese Language Certification β Beijing University of Technology
- Graphic Design β ARENA Multimedia, Islamabad Campus (2015)
Conclusionπ
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 π
π‘ Radar and Engineering
- 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.
- π Type: Article (Open Access)
- π Citations: 0
ποΈ Ophthalmology and AI
- 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.
- π Type: Article (Open Access)
- π Citations: 0
π Errata and Corrections
- 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.
- π Type: Erratum (Open Access)
- π Citations: 1
-
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.
- π Type: Erratum (Open Access)
- π Citations: 0
π§ Diabetic Retinopathy and AI Models
- 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.
- π Type: Article (Open Access)
- π Citations: 49