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

 

 

 

Umesh Kumar Lilhore | Deep Learning | Best Researcher Award

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Dr. Umesh Kumar Lilhore | Deep Learning | Best Researcher Award

Professor at Galgotias University, India

Dr. Umesh Kumar Lilhore is a seasoned Professor and Researcher in Computer Science and Engineering (CSE) at Galgotias University, Greater Noida, India. With over 18 years of experience in academia and research, he has established himself as an expert in Artificial Intelligence (AI), Deep Learning, and Environmental Studies. Dr. Lilhore has earned a Ph.D. and M.Tech in CSE, complemented by a Postdoctoral fellowship from the USA. He has published over 100 research articles in indexed journals, with more than 3,800 citations and an h-index of 29+, showcasing his impactful contributions to the academic community.

Publication Profile 

Scopus

Educational Background 🎓

  • Ph.D.: Computer Science and Engineering (Institution not specified)
  • M.Tech: Computer Science and Engineering (Institution not specified)
  • Postdoctoral Fellowship: USA (Institution not specified)

Professional Experience 💼

  • Designation: Professor, Computer Science and Engineering
  • Institution: Galgotias University, Greater Noida, India
  • Years of Experience: Over 18 years in teaching and research
  • Editorial Appointment: Editorial Board Member, Springer Journal: BMC Medical Informatics and Decision Making
  • Collaborations: National and international collaborations with institutions such as:
    • National University of Science and Technology Politehnica Bucharest
    • Pitesti University Center, Romania
    • University of Louisiana, USA
    • Arab Minch University

Research Interests 🔬

  • Artificial Intelligence (AI)
  • Deep Learning
  • Environmental Studies

Awards and Honors🏆✨

  • Patents:
    • 35 Indian patents
    • 2 UK design patents
  • Books Published: 10+ Scopus-indexed books
  • Projects: Completed AICTE-funded Air Quality Analysis project
  • Professional Memberships: IEEE, ACM

Contributions and Achievements

  • Published 51 SCI-indexed and 102 Scopus-indexed research papers.
  • Google Scholar citation index: 28+ with 3,800+ citations and an h-index of 29+.
  • Collaborated on research projects with prestigious international institutions.
  • Actively engaged in advancing AI and sustainability research.

Conclusion🌟

Dr. Umesh Kumar Lilhore exemplifies excellence in academia, research, and innovation. His prolific contributions to AI, Deep Learning, and Environmental Studies reflect his dedication to addressing critical global challenges. With a strong record of publications, patents, and collaborative projects, he has significantly advanced knowledge and applications in his field. Dr. Lilhore continues to inspire as a thought leader, mentor, and innovator in computer science and engineering.

Publications 📚

📄 Systematic Review on Cardiovascular Disease Detection and Classification
Authors: Pandey, V., Lilhore, U.K., Walia, R.
Journal: Biomedical Signal Processing and Control, 2025, 102, 107329.
📊 Citations: 0

📚 An Attention-Driven Hybrid Deep Neural Network for Enhanced Heart Disease Classification
Authors: Lilhore, U.K., Simaiya, S., Alhussein, M., Aurangzeb, K., Hussain, A.
Journal: Expert Systems, 2025, 42(2), e13791.
📊 Citations: 0

⚠️ Erratum: Hybrid CNN-LSTM Model with Efficient Hyperparameter Tuning for Prediction of Parkinson’s Disease
Authors: Lilhore, U.K., Dalal, S., Faujdar, N., Thangaraju, P., Velmurugan, H.
Journal: Scientific Reports, 2024, 14(1), 27077.
📊 Citations: 0

⚙️ Improving Efficiency and Sustainability via Supply Chain Optimization Through CNNs and BiLSTM
Authors: Dalal, S., Lilhore, U.K., Simaiya, S., Radulescu, M., Belascu, L.
Journal: Technological Forecasting and Social Change, 2024, 209, 123841.
📊 Citations: 0

❤️ Enhancing Heart Disease Classification with M2MASC and CNN-BiLSTM Integration for Improved Accuracy
Authors: Pandey, V., Lilhore, U.K., Walia, R., Baqasah, A.M., Algarni, S.
Journal: Scientific Reports, 2024, 14(1), 24221.
📊 Citations: 0

🧬 Intelligence Model on Sequence-Based Prediction of PPI Using AISSO Deep Concept with Hyperparameter Tuning Process
Authors: Thareja, P., Chhillar, R.S., Dalal, S., Baqasah, A.M., Algarni, S.
Journal: Scientific Reports, 2024, 14(1), 21797.
📊 Citations: 0

🔬 Optimizing Protein Sequence Classification: Integrating Deep Learning Models with Bayesian Optimization for Enhanced Biological Analysis
Authors: Lilhore, U.K., Simiaya, S., Alhussein, M., Dalal, S., Aurangzeb, K.
Journal: BMC Medical Informatics and Decision Making, 2024, 24(1), 236.
📊 Citations: 0

☁️ Optimizing Energy Efficiency in MEC Networks: A Deep Learning Approach with Cybertwin-Driven Resource Allocation
Authors: Lilhore, U.K., Simaiya, S., Dalal, S., Baqasah, A.M., Algarni, S.
Journal: Journal of Cloud Computing, 2024, 13(1), 126.
📊 Citations: 0

🌾 Maize Leaf Disease Recognition Using PRF-SVM Integration: A Breakthrough Technique
Authors: Bachhal, P., Kukreja, V., Ahuja, S., Alroobaea, R., Algarni, S.
Journal: Scientific Reports, 2024, 14(1), 10219.
📊 Citations: 1

✅ Correction: Hybrid CNN-LSTM Model with Efficient Hyperparameter Tuning for Prediction of Parkinson’s Disease
Authors: Lilhore, U.K., Dalal, S., Faujdar, N., Thangaraju, P., Velmurugan, H.
Journal: Scientific Reports, 2024, 14(1), 9335.
📊 Citations: 0