Dr. Abdulrahman Alnaim | Technology | Excellence in Research Award

Dr. Abdulrahman Alnaim | Technology | Excellence in Research Award

Dr. Abdulrahman Alnaim | Technology – Associate Professor at King Faisal University, Saudi Arabia

Dr. Abdulrahman Khalid Alnaim is an accomplished academic and researcher specializing in computer science and information security. With a strong foundation in computer information systems and management information systems, he has dedicated his career to advancing research in emerging technologies such as cybersecurity, cloud computing, and network architecture. His work is characterized by innovative approaches to securing next-generation networks and optimizing system performance, reflecting a commitment to both academic excellence and practical applications in the tech industry.

Profile:

Google Scholar

Education:

Dr. Alnaim earned his Ph.D. in Computer Science from Florida Atlantic University, USA, where he focused on developing secure and efficient computing models. He also holds a Masterโ€™s in Management Information Systems from Nova Southeastern University, USA, which enriched his understanding of integrating technology with business strategies. His academic journey began at King Faisal University, Saudi Arabia, where he completed his Bachelorโ€™s degree in Computer Information Systems, laying the groundwork for his passion for research and technology. This diverse educational background has enabled him to approach complex problems with a multidisciplinary perspective.

Experience:

Dr. Alnaim has served at King Faisal University, Saudi Arabia, in various academic roles. Starting as a Teacher Assistant in 2012, he quickly advanced to become a Lecturer and later an Assistant Professor in the Management Information Systems Department within the School of Business. Throughout his tenure, he has contributed significantly to curriculum development, academic research, and student mentorship. His professional journey reflects a consistent commitment to fostering an environment of academic growth, research innovation, and knowledge dissemination.

Research Interests:

Dr. Alnaimโ€™s research interests lie in the domains of cloud technologies, cybersecurity, and network architecture, with a particular focus on emerging trends like 5G/6G networks, network function virtualization (NFV), and edge computing. His work explores the development of robust security frameworks, optimized resource management strategies, and innovative architectures for next-generation networks. His research not only addresses theoretical challenges but also provides practical solutions for enhancing cybersecurity, system efficiency, and data integrity in complex digital environments.

Awards:

While Dr. Alnaimโ€™s distinguished academic career is marked by numerous achievements, his contributions to research have earned him recognition within the academic community. His work has been cited extensively, reflecting its influence on contemporary studies in cybersecurity and network technologies. His dedication to research excellence is evident through his continuous pursuit of knowledge, innovative problem-solving, and commitment to advancing the field of computer science.

Publications ๐Ÿ“š:

  1. “Zero Trust Strategies for Cyber-Physical Systems in 6G Networks” (2025)Mathematics
    This paper discusses advanced security models tailored for cyber-physical systems in 6G environments. ๐Ÿš€

  2. “Securing 5G Virtual Networks: A Critical Analysis of SDN, NFV, and Network Slicing Security” (2024)International Journal of Information Security
    The article provides an in-depth analysis of security vulnerabilities and countermeasures in 5G networks. ๐Ÿ”

  3. “Trust Management and Resource Optimization in Edge and Fog Computing Using the CyberGuard Framework” (2024)Sensors
    This research introduces the CyberGuard framework for enhancing trust management in edge and fog computing environments. ๐ŸŒ

  4. “Network Slicing in 6G: A Strategic Framework for IoT in Smart Cities” (2024)Sensors
    A strategic approach to optimizing network slicing for IoT applications in smart cities. ๐Ÿ™๏ธ

  5. “Classification of Alzheimerโ€™s Disease Using MRI Data Based on Deep Learning Techniques” (2024)Journal of King Saud University โ€“ Computer and Information Sciences
    This study leverages deep learning models to improve the early detection of Alzheimerโ€™s disease using MRI data. ๐Ÿง 

  6. “Machine-Learning-Based IoTโ€“Edge Computing Healthcare Solutions” (2023)Electronics
    Focuses on integrating machine learning with IoT and edge computing to enhance healthcare services. ๐Ÿ’ก

  7. “A Misuse Pattern for Modifying Non-Control Threats in NFV” (2022)Future Internet
    Proposes a model to identify and mitigate non-control threats in network function virtualization environments. ๐Ÿ–ฅ๏ธ

These publications have collectively garnered significant citations, underscoring their impact on academic research and industry practices. ๐Ÿ“ˆ

Conclusion:

Dr. Abdulrahman Khalid Alnaim exemplifies the qualities of an outstanding researcher, with a robust academic background, extensive research contributions, and a commitment to advancing the field of computer science and information security. His work in cybersecurity, cloud technologies, and network architecture has not only enriched academic discourse but also provided practical solutions to real-world challenges.

His innovative approach, combined with a strong publication record and active involvement in academic and research communities, makes him a deserving candidate for the Excellence in Research Award. Dr. Alnaimโ€™s contributions reflect the values of academic rigor, intellectual curiosity, and a relentless pursuit of knowledge that this prestigious award seeks to honor.

Dr. Chaosai Liu | Technology Applications | Best Researcher Award

Dr. Chaosai Liu | Technology Applications | Best Researcher Award

Dr. Chaosai Liu | Henan University of Technology | China

Liu Chaosai is a distinguished researcher from Henan University of Technology, specializing in grain storage safety theory and its applications. With a long-term commitment to improving maize storage techniques, he has contributed to numerous national and provincial projects, including the National Grain Public Welfare Research Project and Key R&D projects in Henan Province. His research has been instrumental in advancing our understanding of heat, moisture transfer, and fungal growth in stored grains, particularly maize. Liu has published over 20 academic papers and holds six authorized patents. He has earned recognition from both the Henan Provincial Department of Education and the China Grain and Oil Society. ๐ŸŒพ๐Ÿ“š๐Ÿ…

Professional Profile:

ORCID

Suitability for the Best Researcher Award

Liu Chaosai is certainly a strong candidate for the Best Researcher Award based on his significant contributions to the field of grain storage safety. His work at Henan University of Technology has been pivotal in advancing storage techniques for maize, an essential staple crop. Liu’s research has made substantial strides in understanding and mitigating the challenges of grain storage, particularly maize. His focus on heat, moisture transfer, and fungal growth has directly influenced the improvement of storage methods that ensure food security and reduce waste. Liuโ€™s involvement in national and provincial projects, such as the National Grain Public Welfare Research Project and Key R&D projects in Henan Province, further highlights his dedication to advancing the field.

Education & Experience

  • Henan University of Technology – College of Civil Engineering, Ph.D. in Engineering ๐Ÿ”ฌ๐ŸŽ“
  • Henan Key Laboratory of Grain Storage Facility and Safety – Researcher ๐Ÿ”
  • Academy of National Food and Strategic Reservation Administration – Collaborator ๐Ÿ”„
  • National Grain Public Welfare Research Project of China – Project participant ๐Ÿ“Š

Professional Development

Liu has developed a strong portfolio of research in grain storage, focusing on heat and moisture transfer, fungal growth, and the implications of kernel breakage in maize. His professional growth is marked by consistent contributions to national and provincial projects, publication of over 20 papers, and securing six patents in the field of grain storage safety. He has also gained significant practical experience by engaging in simulation systems and experimental research to improve storage methods for maize. His professional development continues to shape innovations in the agricultural sector. ๐Ÿง‘โ€๐Ÿ”ฌ๐Ÿ’ผ๐Ÿ“ˆ

Research Focus

Liu’s research primarily revolves around the study of grain storage safety, with particular attention to maize. He focuses on understanding the effects of temperature, moisture content, and fungal activity on stored grain. A significant part of his work includes studying how kernel breakage impacts heat and moisture distribution, leading to potential storage risks. His research includes developing models to predict temperature changes and fungal growth in maize bulk. By advancing grain storage techniques, Liu aims to minimize post-harvest losses and ensure the safe storage of grains. ๐ŸŒพ๐Ÿงฌ๐Ÿ”ฅ

Awards & Honors

  • Second Prize – Henan Provincial Department of Education ๐Ÿ…
  • Third Prize – China Grain and Oil Society ๐Ÿฅ‰
  • 6 Patents – Authorized Invention Patents ๐Ÿ”
  • 20+ Academic Papers – Published in leading journals ๐Ÿ“–

Publication Top Notes:

  • ๐ŸŒพ Analysis of Heat and Moisture Transfer and Fungi-Induced Hot Spots in Maize Bulk with Different Broken Kernel ContentsAgriculture
  • ๐Ÿ—๏ธ Numerical Simulation of Backfilling Construction for Underground Reinforced Concrete Grain SilosBuildings
  • ๐ŸŒพ Element Tests and Simulation of Effects of Vertical Pressure on Compression and Mildew of WheatComputers and Electronics in Agriculture
  • ๐Ÿ“Š A Scientometric Review of Grain Storage Technology in the Past 15 Years (2007โ€“2022) Based on Knowledge Graph and VisualizationFoods
  • ๐Ÿ—๏ธ Visualization Analysis of Cross Research Between Big Data and Construction Industry Based on Knowledge GraphBuildings

 

 

 

Mr. Asif Mehmood | Artificial intelligence Awards | Best Researcher Award

Mr. Asif Mehmood | Artificial intelligence Awards | Best Researcher Award

Mr. Asif Mehmood, National university of technology, Pakistan

Asif Mehmood is a dedicated professional with a strong academic background and diverse expertise in computer sciences. Currently pursuing a PhD in Computer Sciences at COMSATS University Islamabad, Wah Campus, he holds a Master’s degree and a Bachelor’s degree in the same field. With a keen interest in machine learning and deep learning, Asif has contributed to notable publications in prestigious journals, focusing on human gait recognition and biometric techniques. His experience spans from research associate roles to lecturing positions at HITEC University Taxila, showcasing his commitment to academia and research. Asif’s technical proficiency includes programming languages such as MATLAB, JavaScript, and Java, along with extensive experience in project development and academic projects. He resides in Attock, Punjab, Pakistan, and is open to providing references upon request.

Professional Profile:

Scopus

๐ŸŽ“ Education:

Asif Mehmood has pursued a remarkable academic journey, demonstrating consistent excellence in his educational endeavors. He commenced his formal education with a Bachelor of Science in Computer Sciences (BSCS) from the University of Wah, spanning from 2013 to 2017, where he attained a commendable CGPA of 3.46 out of 4.0. Building upon this foundation, he pursued a Master of Science in Computer Sciences (MSCS) at COMSATS University Islamabad, Wah Campus, from 2018 to 2020, achieving an impressive CGPA of 3.84. Asif further advanced his academic pursuits by undertaking a PhD in Computer Sciences at the same institution, currently in progress, with an outstanding CGPA of 3.94 thus far.

๐Ÿ’ผ Experience:

Asif Mehmood has enriched his professional experience through roles at HITEC University Taxila. He commenced as a Research Associate in January 2022, where he actively contributed to research endeavors until June 2022. Building upon his expertise, Asif transitioned into the role of Lecturer in Computer Science at the same institution in September 2022, a position he currently holds. These roles have allowed Asif to apply his academic knowledge and research skills in a practical setting while also nurturing the next generation of computer science professionals through teaching and mentorship.

๐Ÿ“ Projects:

Asif Mehmood has demonstrated his proficiency in software development and research through various notable projects. Among these, he developed a Document Clustering Search Engine using Java and MySQL, showcasing his skills in both programming and database management. Additionally, his thesis focused on Prosperous Human Gait Recognition, employing Machine Learning techniques within MATLAB, highlighting his expertise in this advanced field. Furthermore, Asif has undertaken diverse academic projects encompassing Assembly Language programming, Android app development, and web development, reflecting his versatility and innovative approach to problem-solving in the realm of computer science.

Publication Top Notes:

  1. Human Gait Recognition by using Two Stream Neural Network along with Spatial and Temporal Features
    • Authors: Mehmood, A.; Amin, J.; Sharif, M.; Kadry, S.
    • Journal: Pattern Recognition Letters, 2024, 180, pp. 16โ€“25
    • Citations: 0
  2. Prosperous Human Gait Recognition: an end-to-end system based on pre-trained CNN features selection
    • Authors: Mehmood, A.; Khan, M.A.; Sharif, M.; Riaz, N.; Ashraf, I.
    • Journal: Multimedia Tools and Applications, 2024, 83(5), pp. 14979โ€“14999
    • Citations: 24
  3. TS2HGRNet: A paradigm of two stream best deep learning feature fusion assisted framework for human gait analysis using controlled environment in smart cities
    • Authors: Khan, M.A.; Mehmood, A.; Kadry, S.; Alsubai, S.; Alqatani, A.
    • Journal: Future Generation Computer Systems, 2023, 147, pp. 292โ€“303
    • Citations: 3
  4. Human gait analysis for osteoarthritis prediction: a framework of deep learning and kernel extreme learning machine
    • Authors: Khan, M.A.; Kadry, S.; Parwekar, P.; Khan, J.A.; Naqvi, S.R.
    • Journal: Complex and Intelligent Systems, 2023, 9(3), pp. 2665โ€“2683
    • Citations: 23
  5. Human gait recognition: A deep learning and best feature selection framework
    • Authors: Mehmood, A.; Khan, M.A.; Tariq, U.; Mostafa, R.R.; ElZeiny, A.
    • Journal: Computers, Materials and Continua, 2021, 70(1), pp. 343โ€“360
    • Citations: 8