Bader Alsharif | Computer Science | Best Innovation Award

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Dr. Bader Alsharif | Computer Science | Best Innovation Award

Florida Atlantic University, United States

Dr. Bader Alsharif is an accomplished PhD candidate in Computer Engineering with a strong background in teaching, technical support, and curriculum development. He has led innovative projects, including the first CISCO simulation lab in Saudi Arabia, and has managed over 300 devices, optimizing performance and security. With a focus on AI, Cybersecurity, and IoT, particularly in healthcare, Dr. Alsharif has published over 7 peer-reviewed papers. He has demonstrated leadership in both academic and technical spheres, guiding over 200 students and advocating for special needs education, ensuring their academic success. His expertise extends to training professionals, having conducted comprehensive courses for Saudi Telecom employees. Dr. Alsharif has shown a profound commitment to advancing technology and fostering inclusivity, particularly through his work with individuals with special needs. His work bridges technological innovation with social impact, positioning him as a forward-thinking leader in computer engineering and healthcare.

Professional ProfileĀ 

Education

Dr. Bader Alsharif has an extensive academic background, beginning with a Bachelor of Science in Computer Engineering from the College of Technology in Riyadh, Saudi Arabia, where he graduated in 2008. He further advanced his studies with a Master of Science in Computer Engineering from the Florida Institute of Technology, completing his degree in 2017. Currently, Dr. Alsharif is pursuing a Doctor of Computer Engineering at Florida Atlantic University in Boca Raton, USA, with an expected graduation date of 2025. His academic journey has been marked by a strong focus on integrating Artificial Intelligence (AI), Cybersecurity, and Internet of Things (IoT) technologies, particularly in healthcare applications. This multidisciplinary education has provided Dr. Alsharif with the expertise to contribute meaningfully to both research and practical innovations in these fields, bridging the gap between technology and real-world healthcare challenges.

Professional Experience

Dr. Bader Alsharif has a diverse professional background with extensive experience in both academia and technical roles. He currently serves as a Teaching Assistant at Florida Atlantic University, where he guides and evaluates over 30 students on engineering design projects and assists more than 200 students with project development and technical issues. Prior to this, Dr. Alsharif held a prominent role as a Lecturer at the Communications and Information College in Riyadh, Saudi Arabia, where he managed and maintained over 300 devices and led the installation of the first CISCO simulation lab in the country. This project, a significant innovation, involved the deployment of over 30 devices and routers. He also trained 100 employees from Saudi Telecom and designed assessments for instructors working with special needs students. Dr. Alsharifā€™s professional experience reflects a strong blend of technical expertise, leadership, and a commitment to education and inclusivity.

Research Interest

Dr. Bader Alsharifā€™s research interests lie at the intersection of Artificial Intelligence (AI), Cybersecurity, and the Internet of Things (IoT), with a particular focus on their applications in healthcare. He is deeply committed to exploring how these advanced technologies can be integrated to enhance patient outcomes and improve healthcare systems. His work aims to leverage AI algorithms to optimize medical data analysis, while also addressing critical security concerns in the rapidly growing field of IoT healthcare devices. Dr. Alsharifā€™s research also extends to the development of innovative solutions for securing healthcare networks and ensuring the privacy of sensitive patient information. With a strong academic foundation and several peer-reviewed publications, he is dedicated to advancing knowledge in these areas and exploring how cutting-edge technologies can be applied to solve real-world challenges in healthcare. His work demonstrates a commitment to both technological innovation and social impact, especially in the realm of health and well-being.

Award and Honor

Dr. Bader Alsharif has received numerous accolades for his contributions to academia and technology. His achievements include successfully leading the installation of the first CISCO simulation lab in Saudi Arabia, which became a groundbreaking project in the region, significantly enhancing the educational infrastructure for telecommunications. In recognition of his exceptional performance in teaching and technical support, he consistently achieved high job performance ratings, including scores no less than 99/100. Dr. Alsharif has also been honored for his commitment to inclusive education, particularly in advocating for and supporting students with special needs, ensuring their academic excellence. His research in AI, Cybersecurity, and IoT, particularly in the healthcare sector, has earned him recognition as a published researcher with over 7 peer-reviewed papers. Through his work, Dr. Alsharif has received recognition from academic institutions and industry professionals for his innovative contributions, leadership, and commitment to fostering technological advancements with social impact.

Conclusion

Bader Alsharif has demonstrated significant innovation across several key areas of AI, Cybersecurity, and IoT, particularly in healthcare. His leadership in education and advocacy for special needs individuals also reflects a deep commitment to both technological advancement and social impact. His ability to lead high-profile projects and publish extensively in relevant fields positions him as a strong candidate for the Best Innovation Award. However, expanding his research impact and involvement in larger-scale, cross-disciplinary projects could further elevate his candidacy. Overall, he has the potential to be an exceptional award recipient based on his innovative contributions and impact.

Publications Top Noted

  • Title: Deep learning technology to recognize American Sign Language alphabet
    Authors: B Alsharif, AS Altaher, A Altaher, M Ilyas, E Alalwany
    Year: 2023
    Citations: 14
  • Title: Internet of things technologies in healthcare for people with hearing impairments
    Authors: B Alsharif, M Ilyas
    Year: 2022
    Citations: 8
  • Title: Deep Learning Technology to Recognize American Sign Language Alphabet Using Multi-Focus Image Fusion Technique
    Authors: B Alsharif, M Alanazi, AS Altaher, A Altaher, M Ilyas
    Year: 2023
    Citations: 6
  • Title: Machine Learning Technology to Recognize American Sign Language Alphabet
    Authors: B Alsharif, M Alanazi, M Ilyas
    Year: 2023
    Citations: 4
  • Title: Enhancing cybersecurity in healthcare: Evaluating ensemble learning models for intrusion detection in the internet of medical things
    Authors: T Alsolami, B Alsharif, M Ilyas
    Year: 2024
    Citations: 3
  • Title: Multi-Dataset Human Activity Recognition: Leveraging Fusion for Enhanced Performance
    Authors: M Alanazi, B Alsharif, AS Altaher, A Altaher, M Ilyas
    Year: 2023
    Citations: 3
  • Title: Transfer learning with YOLOV8 for real-time recognition system of American Sign Language Alphabet
    Authors: B Alsharif, E Alalwany, M Ilyas
    Year: 2024
    Citations: 1
  • Title: Franklin Open
    Authors: B Alsharif, E Alalwany, M Ilyas
    Year: 2024
    Citations: Not available yet

Meiyan Liang | Computer Science | Best Researcher Award

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šŸŒŸAssoc Prof Dr. Meiyan Liang, Computer Science, Best Researcher Award šŸ†

  • Ā Associate Professor at Shanxi University, China

Meiyan Liang, PhD, is an accomplished researcher in the field of Instrument Science and Technology, with a focus on Deep Learning and Medical Image Processing. Currently affiliated with the School of Physics and Electronic Engineering at Shanxi University in China, Dr. Liang completed her PhD at the Opto-Electronic College, Beijing Institute of Technology. She has made significant contributions to the development of innovative technologies for the identification and classification of various medical conditions, particularly in cancer diagnosis. Her work spans both theoretical and experimental domains, with a particular emphasis on leveraging neural networks and terahertz imaging techniques. Dr. Liang’s expertise is recognized through numerous awards, patents, and a prolific publication record in prestigious journals.

Author Metrics

Scopus Profile

ORCID Profile

Dr. Liang’s research output is not only extensive but also impactful, as evidenced by her author metrics. She has consistently published in high-impact journals, demonstrating the significance of her work within the scientific community. Additionally, Dr. Liang’s patents highlight her innovative approach to problem-solving and technology development.

  • Citations: 138 citations across 136 documents
  • Documents: Authored 25 documents
  • h-index: 5

Education

Dr. Meiyan Liang obtained her PhD in Instrument Science and Technology from the Opto-Electronic College at Beijing Institute of Technology. Her doctoral research focused on the application of deep learning methodologies in medical image processing, particularly for cancer diagnosis.

Research Focus

Dr. Liang’s research primarily centers around two main areas: Deep Learning and Medical Image Processing. Within these domains, she specializes in utilizing neural networks for the interpretation and analysis of medical images, with a particular emphasis on cancer detection and classification. Her work also involves the integration of advanced imaging techniques, such as terahertz imaging, to develop novel diagnostic tools.

Professional Journey

Following her doctoral studies, Dr. Liang embarked on a professional journey that has seen her become an esteemed researcher in the field of medical imaging. She has held positions at various academic institutions, including her current role at Shanxi University. Throughout her career, Dr. Liang has secured research funding, published extensively, and obtained several patents for her innovative contributions to the field.

Honors & Awards

Dr. Liang’s outstanding contributions to her field have been recognized through numerous honors and awards. Notable accolades include being awarded the “Sanjin talent” by the government of Shanxi Province and receiving the “China Instrument & Control Society Scholarship” from the Chinese instrumentation society.

Research Timeline

Dr. Liang’s research timeline showcases her progression as a researcher and the evolution of her research interests. Starting from her doctoral studies, she has continued to expand her expertise and contribute to advancements in medical imaging technology. Her research timeline reflects a commitment to excellence and a dedication to addressing critical challenges in healthcare through innovative research.

Publications Noted & Contributions

Dr. Liang has made significant contributions to the academic community through her prolific publication record. Her research findings have been published in prestigious journals such as the IEEE Journal of Biomedical and Health Informatics, Computer Methods and Programs in Biomedicine, and The Visual Computer. These publications cover a wide range of topics, including interpretable inference, whole-slide image prediction, and pathology image restoration.

Title: Interpretable Inference and Classification of Tissue Types in Histological Colorectal Cancer Slides Based on Ensembles Adaptive Boosting Prototype Tree

  • Authors: Liang, M., Wang, R., Liang, J., Zhang, T., Zhang, C.
  • Journal: IEEE Journal of Biomedical and Health Informatics, 2023, 27(12), pp. 6006ā€“6017
  • Abstract: This paper presents a method for interpretable inference and classification of tissue types in histological colorectal cancer slides using ensembles adaptive boosting prototype tree.

Title: Multi-scale self-attention generative adversarial network for pathology image restoration

  • Authors: Liang, M., Zhang, Q., Wang, G., Liu, H., Zhang, C.
  • Journal: Visual Computer, 2023, 39(9), pp. 4305ā€“4321
  • Abstract: This paper introduces a multi-scale self-attention generative adversarial network for pathology image restoration.
  • Citations: 1

Title: Interpretable classification of pathology whole-slide images using attention based context-aware graph convolutional neural network

  • Authors: Liang, M., Chen, Q., Li, B., Jiang, X., Zhang, C.
  • Journal: Computer Methods and Programs in Biomedicine, 2023, 229, 107268
  • Abstract: This paper proposes an interpretable classification method for pathology whole-slide images using an attention-based context-aware graph convolutional neural network.
  • Citations: 6

Title: A novel strategy regarding geometric product for liquids discrimination based on THz reflection spectroscopy

  • Authors: Liu, H., Liu, X., Zhang, Z., Liang, M., Zhang, C.
  • Journal: Spectrochimica Acta – Part A: Molecular and Biomolecular Spectroscopy, 2022, 274, 121104
  • Abstract: This paper proposes a novel strategy for liquids discrimination based on THz reflection spectroscopy using the geometric product.
  • Citations: 1

Title: THz ISAR imaging using GPU-accelerated phase compensated back projection algorithm

  • Authors: Liang, M.-Y., Ren, Z.-Y., Li, G.-H., Zhang, C.-L., Fathy, A.E.
  • Journal: Hongwai Yu Haomibo Xuebao/Journal of Infrared and Millimeter Waves, 2022, 41(2), pp. 448ā€“456
  • Abstract: This paper presents THz ISAR imaging using a GPU-accelerated phase-compensated back projection algorithm.
  • Citations: 3