SeongJeong Yoon | Computer Science | Best Researcher Award

Published on by Global Scholar Awards

Best Researcher Award

SeongJeong Yoon
Swiss School of Management

SeongJeong Yoon
Affiliation Swiss School of Management
Country South Korea
Subject Area Computer Science
Event Global Scholar Awards
ORCID 0000-0001-5188-801X

SeongJeong Yoon is affiliated with the Swiss School of Management and is recognized for scholarly contributions in Computer Science through research that supports technological innovation, intelligent computing, digital transformation, and interdisciplinary collaboration. The academic profile reflects sustained engagement with internationally indexed publications and professional research activities that contribute to contemporary scientific knowledge and practical applications within computing disciplines.[1]

Abstract

SeongJeong Yoon has developed an academic profile centered on Computer Science, emphasizing intelligent information systems, digital innovation, software engineering, data analytics, artificial intelligence, cloud technologies, cybersecurity, and emerging computational methodologies. Research activities demonstrate consistent engagement with internationally indexed publications, interdisciplinary collaborations, and knowledge dissemination through scholarly communication. The work contributes to technological advancement by integrating theoretical understanding with practical implementation while addressing contemporary scientific and industrial challenges. Continued participation in academic research reflects commitment to innovation, evidence-based investigation, sustainable digital transformation, and the advancement of global computing knowledge through impactful scholarly contributions and collaborative scientific excellence.[1][2]

Keywords

Artificial Intelligence, Machine Learning, Data Analytics, Software Engineering, Intelligent Systems, Digital Transformation, Cloud Computing, Cybersecurity, Information Systems, Deep Learning, Big Data, Computer Vision.

Introduction

SeongJeong Yoon advances Computer Science through interdisciplinary investigations integrating intelligent computing, software development, and digital technologies. Academic activities emphasize rigorous methodology, collaborative research, and internationally visible publications that strengthen technological innovation while supporting practical applications, sustainable development, and continued scientific progress across evolving computational environments.[1]

Research Profile

SeongJeong Yoon maintains an internationally oriented research profile supported by scholarly publications, institutional collaboration, and participation within modern computing disciplines. Research interests encompass intelligent systems, digital innovation, information technologies, and computational problem solving while contributing to knowledge exchange across academic and professional scientific communities worldwide.[2]

Research Contributions

SeongJeong Yoon contributes through scholarly investigations exploring advanced computing technologies, analytical methodologies, and innovative digital solutions. Research integrates theoretical concepts with practical implementation, encouraging interdisciplinary collaboration while supporting technological advancement, academic excellence, and sustainable innovation across diverse Computer Science research applications.[3]

Publications

SeongJeong Yoon has authored and collaborated on scholarly publications addressing contemporary Computer Science themes including artificial intelligence, software engineering, information systems, cloud computing, and digital transformation. Published research demonstrates methodological consistency, academic relevance, and valuable contributions supporting evidence-based technological development within international scientific literature.[2]

Research Impact

SeongJeong Yoon demonstrates measurable research impact through internationally indexed publications, scholarly visibility, citation activity, and interdisciplinary engagement. Academic contributions encourage knowledge transfer, technological innovation, and collaborative scientific advancement while supporting future investigations addressing emerging computational challenges across academic and industrial environments.[4]

Award Suitability

SeongJeong Yoon demonstrates qualities consistent with recognition through the Best Researcher Award by maintaining sustained scholarly productivity, international academic engagement, and impactful Computer Science research. Professional achievements illustrate commitment to innovation, scientific integrity, collaborative excellence, and meaningful contributions benefiting contemporary global research communities.[5]

Conclusion

SeongJeong Yoon represents an accomplished academic whose Computer Science research supports technological advancement through interdisciplinary scholarship, internationally indexed publications, and collaborative scientific engagement. Continued research activities reinforce professional excellence while contributing valuable knowledge that advances innovation, digital transformation, and sustainable computing research worldwide.[1]

References

  1. Moon, J.-H., Kim, N., Kim, W., & Yoon, S. (2024). A research on the technological elements of the digital twin operation platform in the industrial metaverse federation. https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE11933357
  2. ORCID. (n.d.). ORCID record for SeongJeong Yoon.
    https://orcid.org/0000-0001-5188-801X
  3. Kim, N., Kim, W., & Yoon, S. (2024). Field empirical research on generative artificial intelligence job file generation and worker behavior issues.
    https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE11742484
  4. Choi, J., Kim, N., Kim, W., & Yoon, S. (2023). Research on trends and key issues in industrial collaborative robots and worker interaction.
    https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE11509571
  5. Global Scholar Awards. (n.d.). Best Researcher Award Recognition.
    https://globalscholarawards.com/

Mazen Ramadhan | Computer Science | Innovative Research Award

Published on by Global Scholar Awards

Innovative Research Award

Mazen Ramadhan
Multimedia University, Malaysia

Mazen Ramadhan
Affiliation Multimedia University
Country Malaysia
Scopus ID 57215557743
Documents 16
Citations 176
h-index 6
Subject Area Computer Science
Event Global Scholar Awards
ORCID 0000-0001-9555-7781

Mazen Ramadhan is a researcher at Multimedia University, Malaysia, whose scholarly work primarily focuses on computer science, intelligent systems, cybersecurity, machine learning, digital technologies, and applied computing. His research demonstrates interdisciplinary collaboration and addresses practical technological challenges through innovative computational methods. With publications indexed in major academic databases and measurable citation impact, his contributions have supported advancements in emerging digital technologies and continue to influence research within computer science and related engineering disciplines.[1]

Abstract

Mazen Ramadhan has established a research portfolio centered on computer science with emphasis on cybersecurity, intelligent systems, machine learning, software engineering, digital transformation, and data-driven technologies. His scholarly publications demonstrate practical applications of computational techniques for addressing contemporary technological problems while encouraging interdisciplinary collaboration. Through peer-reviewed research, measurable citation performance, and international academic visibility, his work contributes to knowledge development in emerging digital domains. The consistency of his publications, collaborative research activities, and recognized academic profile reflect sustained contributions to advancing innovation, computational methodologies, and applied scientific research within the global computer science community.[2]

Keywords

Cybersecurity, Machine Learning, Artificial Intelligence, Internet of Things, Software Engineering, Deep Learning, Computer Networks, Data Analytics, Intelligent Systems, Cloud Computing, Digital Transformation, Information Security.

Introduction

Mazen Ramadhan conducts research addressing modern computing challenges through interdisciplinary methods integrating artificial intelligence, cybersecurity, and software technologies. His publications reflect practical problem solving, collaborative investigation, and continuous engagement with emerging digital innovations supporting academic advancement and technological development across diverse computer science applications.[3]

Research Profile

Mazen Ramadhan maintains an internationally visible research profile supported by Scopus, Google Scholar, ORCID, ResearchGate, and institutional records. His publication metrics demonstrate consistent scholarly productivity, interdisciplinary collaboration, and citation impact within computer science, reflecting recognized academic participation in global research communities.[1]

Research Contributions

Mazen Ramadhan contributes to advancing intelligent computing by investigating secure digital systems, machine learning applications, software engineering practices, and innovative computational methodologies. His research supports practical implementations while encouraging multidisciplinary collaboration, enabling improvements in technology adoption, cybersecurity resilience, and intelligent information processing.[4]

Publications

Mazen Ramadhan has authored peer-reviewed publications indexed by Scopus and Google Scholar covering cybersecurity, artificial intelligence, machine learning, digital technologies, and software engineering. These publications demonstrate methodological diversity, collaborative research, and meaningful academic dissemination across recognized international journals and conference proceedings.[2]

Research Impact

Mazen Ramadhan has achieved measurable research influence through citations, indexed publications, and collaborative scientific activities. His scholarly output supports ongoing developments in computer science while contributing evidence-based knowledge that benefits researchers, practitioners, and future investigations across intelligent digital technologies and computational innovation.[1]

Award Suitability

Mazen Ramadhan demonstrates qualifications appropriate for the Innovative Research Award through sustained publication activity, interdisciplinary computer science research, international academic visibility, and measurable scholarly impact. His research achievements illustrate innovation, scientific consistency, and meaningful contributions supporting technological advancement and global academic collaboration.[5]

Conclusion

Mazen Ramadhan continues contributing to computer science through interdisciplinary research, impactful scholarly publications, and international collaboration. His academic profile reflects sustained scientific productivity, practical innovation, and commitment to advancing intelligent digital technologies, supporting recognition within prestigious international research and innovation award programs.[2]

External Links

References

  1. Elsevier. (n.d.). Scopus Author Details: Mazen Ramadhan, Author ID 57215557743. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57215557743
  2. Google Scholar. (n.d.). Mazen Ramadhan Citation Profile.
    https://scholar.google.com/citations?user=-vuQJ7IAAAAJ&hl=en&oi=ao
  3. Multimedia University. (n.d.). Academic Expert Profile: Mazen Ramadhan.
    https://mmuexpert.mmu.edu.my/ramadhanmazen
  4. ORCID. (n.d.). Mazen Ramadhan Research Record.
    https://orcid.org/0000-0001-9555-7781
  5. IEEE. (2019). Representative publication in intelligent computing.
    https://doi.org/10.1109/ACCESS.2020.2970475

Bin Liu | Computer Science | Research Excellence Award

Published on by Global Scholar Awards

Prof. Bin Liu | Computer Science | Research Excellence Award

Professor | Northwest A&F University | China

Prof. Bin Liu is a researcher at Northwest A&F University, Yangling, China, with expertise in artificial intelligence, computer vision, agricultural informatics, and large-scale model training. He has published 69 Scopus-indexed documents, receiving approximately 2,949 citations and achieving an h-index of 18, reflecting sustained academic impact. His recent work focuses on multi-source data fusion, multimodal learning, remote sensing change detection, and efficient parallel training pipelines for large models, with publications in reputable venues such as IEEE Transactions on Computers, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, and Applied Sciences. Liu has collaborated with over 140 co-authors, demonstrating strong interdisciplinary and international research engagement. His research contributes to societal needs by advancing intelligent agricultural disease diagnosis, improving crop monitoring, and enhancing the efficiency of large-scale AI systems, supporting sustainable agriculture and data-driven environmental management.

Citation Metrics (Scopus)

2949
2200
1500
700
0

Citations

2,949

Documents

69

h-index

18

Citations

Documents

h-index

View Scopus Profile
 View Scopus Profile

Featured Publications


MDS-Net: An image-text enhanced multimodal dual-branch Siamese network for remote sensing change detection


– IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2025

PRT: An efficient pipeline reuse technology for large models training


– IEEE International Conference on Cluster Computing (CLUSTER), 2025

VMF-SSD: A novel V-space based multi-scale feature fusion SSD for apple leaf disease detection


– IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2023

Aleeza Adeel | Computer Science | Research Excellence Award

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Mrs. Aleeza Adeel | Computer Science | Research Excellence Award

The University of Waikato | New Zealand

Mrs. Aleeza Adeel is a Ph.D. student at the School of Computing and Mathematical Sciences, University of Waikato, New Zealand, specializing in digital twin frameworks, sustainable energy systems, and user-centered computing solutions. Her research focuses on developing interoperable and scalable digital twin technologies to optimize energy system management, enhance operational efficiency, and support sustainable resource utilization. She has contributed to peer-reviewed publications, including a recent article in Energies on an interoperable user-centered digital twin framework, demonstrating her commitment to integrating advanced computational models with real-world energy systems. Aleeza collaborates with interdisciplinary researchers, including experts in energy management and computational modeling, to ensure her work addresses both technical rigor and societal relevance. Her research contributes to sustainable energy transitions by providing data-driven, user-centric solutions that improve system performance, reduce environmental impact, and support informed decision-making in complex energy infrastructures.

Profile: View ORCID ProfileΒ 

Featured Publication


An Interoperable User‑Centred Digital Twin Framework for Sustainable Energy System Management

– Adeel, A., Apperley, M., & Walmsley, T. G., Energies, 2026, 19(2), Article 333

Miroslaw Kozielski | Computer Science | Best Researcher Award

Published on by Global Scholar Awards

Mr. Miroslaw Kozielski | Computer Science | Best Researcher Award

Kazimierz Wielki University | Poland

Mr. MirosΕ‚aw Kozielski is a researcher at Kazimierz Wielki University in Bydgoszcz, Poland, specializing in computer science, with a strong focus on natural language processing (NLP), industrial informatics, and Industry 4.0/5.0 technologies. His research addresses the use of intelligent language-based systems for automated industrial documentation, knowledge representation, and digital transformation in modern manufacturing environments. He has authored 7 peer-reviewed publications, which have accumulated 35 citations, and holds an h-index of 3, reflecting a focused and emerging academic impact. Dr. Kozielski collaborates with interdisciplinary teams, contributing to the integration of artificial intelligence with industrial and organizational processes. His work supports the development of efficient, human-centric, and sustainable industrial systems, with societal impact through improved documentation quality, enhanced knowledge accessibility, and the practical adoption of advanced AI-driven solutions in contemporary industrial ecosystems.

Citation Metrics (Scopus)

35
25
15
5
0

Citations

35

Documents

7

h-index

3

Citations

Documents

h-index

View Scopus Profile
 View ORCID Profile

Featured Publications

Zeba Shamsi | Computer Science | Research Excellence Award

Published on by Global Scholar Awards

Assoc. Prof. Dr. Zeba Shamsi | Computer Science | Research Excellence Award

Associate Professor | Lendi Institute of Engineering and Technology | India

Dr. Zeba Shamsi is a researcher at the National Institute of Technology Silchar, India, with expertise in computer science and engineering, particularly in cybersecurity, machine learning, and intelligent data-driven systems. Her research focuses on advanced threat detection, deep learning architectures, and generative models for secure and resilient computing. She has authored 7 peer-reviewed research publications, receiving 104 citations, with an h-index of 5, reflecting steady academic impact. Her recent work on zero-day attack detection using dynamic-weighted contractive autoencoders and GAN-based evaluation highlights her contribution to next-generation cyber defense mechanisms. Dr. Shamsi actively collaborates with national and international researchers, fostering interdisciplinary research and knowledge exchange. Her work contributes to improving digital security, protecting critical infrastructure, and supporting safer adoption of emerging technologies, demonstrating meaningful societal and technological impact at both academic and applied levels.

Citation Metrics (Scopus)

104
80
60
40
0

Citations

104

Documents

7

h-index

5

Citations

Documents

h-index

View Google Scholar Profile
 View Scopus Profile
 View ORCID Profile

Featured Publications


An Encryption Scheme for Securing Multiple Medical Images


– Journal of Information Security and Applications, 2019

Visually Meaningful Cipher Data Concealment


– Digital Signal Processing, 2024

Visually Meaningful Cipher Data Concealment


– Digital Signal Processing, 2024

Securing Encrypted Image Information in Audio Data


– Multimedia Tools and Applications, 2023

Naeem Ullah | Computer Science | Best Researcher Award

Published on by Global Scholar Awards

Mr. Naeem Ullah | Computer Science | Best Researcher Award

PhD Student at Software Engineering Research Group (SERG-UOM) University of Malakand, Pakistan

Mr. Naeem Ullah is a dedicated academic and researcher currently pursuing a PhD in Computer Science, with a focus on cybersecurity challenges in vehicle-to-vehicle communication from a software engineering perspective. Holding a strong academic record with a CGPA of 3.75/4.00, he has presented his research at international forums, such as the 2nd Annual International Workshop on Software Engineering, where he shared his Multivocal Literature Review (MLR) protocol on cybersecurity culture. Mr. Ullah has also received recognition for his teaching excellence, earning the Best Teacher Award in 2018. His work experience includes roles as a lecturer at the University Model College KPK, part-time tutor at Allama Iqbal Open University, and facilitator for continuous professional development programs for teachers. His research, currently under review, addresses crucial cybersecurity issues in vehicle-to-vehicle communications. Mr. Ullah’s commitment to furthering his knowledge is evident through multiple certifications in data science, networking, and cybersecurity.

Professional ProfileΒ 

Education

Mr. Naeem Ullah has a strong educational background in Computer Science. He is currently pursuing a PhD in Computer Science with a focus on cybersecurity challenges in vehicle-to-vehicle communication, maintaining an impressive CGPA of 3.75/4.00. His research aims to develop a mitigation model for cybersecurity issues in connected vehicle systems, reflecting his deep engagement with current technological challenges. Mr. Ullah completed his Master’s degree in Computer Science in 2019, achieving a CGPA of 3.7/4.00, with his thesis titled Software Development Process Improvement Model for Small Pakistani Software Development Companies. He also holds a Bachelor’s degree in Computer Science from 2014, with a CGPA of 3.62/4.00. His final year project, Auction Management System, showcased his ability to apply practical solutions to real-world problems. Mr. Ullah’s academic journey is marked by consistent excellence and a strong commitment to advancing his expertise in the field of computer science.

Professional Experience

Mr. Naeem Ullah has accumulated diverse professional experience in both academic and research roles. He has served as a Lecturer in Computer Science at the University Model College KPK, Peshawar, Pakistan, where he taught and mentored students in various computer science subjects. In addition, he has worked as a part-time tutor for Allama Iqbal Open University, Islamabad, since 2022, focusing on Information and Communication Technologies (ICT). Mr. Ullah has also contributed to teacher development programs, serving as a facilitator for the Continuous Professional Development (CPD) of Primary School Teachers (PSTs) through the Provincial Institute of Teacher Education (PITE) in KPK. His role as a part-time researcher at the Department of Computer Science and IT at the University of Malakand further underscores his involvement in academic research. Earlier in his career, he worked as a Secondary School Teacher at the Elementary and Secondary Education Department, KPK. His experiences reflect a blend of teaching, research, and educational development.

Research Interest

Mr. Naeem Ullah’s research interests primarily focus on cybersecurity, particularly in the context of emerging technologies such as vehicle-to-vehicle (V2V) communication. His PhD research investigates cybersecurity challenges and proposes mitigation models for securing V2V communication systems from a software engineering perspective. This area of research is highly relevant due to the increasing integration of connected vehicles and the need for secure communication protocols to protect sensitive data. Additionally, Mr. Ullah is interested in software engineering, with a particular emphasis on improving software development processes for small software companies in Pakistan, as demonstrated in his Master’s thesis. He has also contributed to the field of cybersecurity culture through his work on a Multivocal Literature Review (MLR) protocol, which identifies cybersecurity challenges and best practices in V2V communication. His research endeavors aim to address critical issues in both cybersecurity and software engineering, contributing to the development of safer, more efficient technologies.

Award and Honor

Mr. Naeem Ullah has received notable recognition for his academic and professional achievements. In 2022, he presented his Multivocal Literature Review (MLR) Protocol at the 2nd Annual International Workshop on Software Engineering (WSE-2022), organized by the Software Engineering Research Group at the University of Malakand. This presentation, focused on Cybersecurity Culture, showcased his expertise and contribution to the field of cybersecurity. Additionally, Mr. Ullah earned the prestigious Best Teacher Award from the Director of Elementary and Secondary Education, KPK, Pakistan, in 2018. This recognition highlights his excellence in teaching and his commitment to fostering the growth and development of his students. These awards and honors reflect Mr. Ullah’s dedication to advancing both his academic research and educational practices, demonstrating his commitment to the fields of computer science and cybersecurity while contributing positively to the educational community.

Conclusion

Naeem Ullah is a promising candidate for the Best Researcher Award, with a solid academic record, a focused and impactful research topic, and a commitment to both education and professional development. His strengths lie in his dedication to advancing cybersecurity research in emerging technologies like vehicle-to-vehicle communication and his capacity for leadership in educational initiatives. To further enhance his candidacy, Naeem could focus on increasing his research output, expanding his research scope, and engaging more in international collaborations to elevate the impact of his work.

Publications Top Noted

  • Title: Solutions to Cybersecurity Challenges in Secure Vehicle-to-Vehicle Communications: A Multivocal Literature Review
    Authors: Naeem Ullah, S.U. Khan, M. Niazi, A.A. Khan, J.A. Nasir
    Journal: Information and Software Technology
    Year: 2025
    Volume: 179
    Article ID: 107639
    Citations: 0
  • Title: Challenges and Their Practices in Adoption of Hybrid Cloud Computing: An Analytical Hierarchy Approach
    Authors: S.U. Khan, H.U. Khan, Naeem Ullah, R.A. Khan
    Journal: Security and Communication Networks
    Year: 2021
    Article ID: 1024139
    Citations: 2
  • Title: Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review
    Authors: S. Nazir, Y. Ali, Naeem Ullah, I. GarcΓ­a-MagariΓ±o
    Journal: Wireless Communications and Mobile Computing
    Year: 2019
    Article ID: 5931315
    Citations: 138
  • Title: Practices for Clients in the Adoption of Hybrid Cloud
    Authors: S.U. Khan, Naeem Ullah
    Journal: Proceedings of the Pakistan Academy of Sciences: Part A
    Year: 2017
    Volume: 54(1A)
    Pages: 13–32
    Citations: 3

Bader Alsharif | Computer Science | Best Innovation Award

Published on by Global Scholar Awards

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 ProfileΒ 

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. Alsharif’s professional experience reflects a strong blend of technical expertise, leadership, and a commitment to education and inclusivity.

Research Interest

Dr. Bader Alsharif’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. Alsharif’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

Himanshi Babbar | Networking | Best Researcher Award

Published on by Global Scholar Awards

Himanshi Babbar | Networking | Best Researcher Award

Dr . HimanshiBabbar ,Chitkara University Institute of Engineering and Technology , India

Dr. Himanshi Babbar is an accomplished academic with extensive experience in the field of computer science and technology. She currently serves as an Assistant Professor, Research (CURIN) at Chitkara University, where she has been since February 2022. Her prior roles include working as a Full-time Research Scholar at Chitkara University and as an Assistant Professor at the Chandigarh Group of Colleges and Aryans Group of Colleges. Her teaching portfolio spans a range of undergraduate and postgraduate courses, including Computer Networks, Database Management Systems, Web Technologies, and Programming in various languages. Dr. Babbar’s research interests are centered around advanced networking topics such as Software Defined Networking (SDN), Internet of Things (IoT), Intrusion Detection Systems (IDS), and Deep Learning. Her work aims to enhance network efficiency, security, and integration with emerging technologies.

Publication profile

google scholar

Scopus Profile

ORCID

Education

Himanshi Babbar has an extensive and impressive educational background. She completed her Postdoctoral research at Zayed University, a public university in the UAE, from 2021 to 2022. Following this, she earned her PhD from Chitkara University, Punjab, a private university, between 2018 and 2021. Both of these prestigious qualifications were awarded upon completion. Prior to her PhD, Himanshi completed her Master of Computer Applications (MCA) at Chitkara University, Punjab, from 2012 to 2015, achieving a CGPA of 7.91. She also holds a Bachelor of Computer Applications (BCA) from Chitkara Institute of Engineering and Technology, Punjab, under Punjab Technical University, where she graduated with an impressive 83.0% between 2009 and 2012. Her earlier education includes completing Class XII at ICL Public School in Rajpura under the CBSE board in 2009, with a percentage of 72.6%. She also completed her Class X education at the same school in 2007, securing a percentage of 57.8%

Experience

Dr. Himanshi Babbar is currently serving as an Assistant Professor, Research (CURIN) at Chitkara University, Rajpura, Punjab Campus, since February 2022. Before this role, she was a Full-time Research Scholar at the same institution from November 2018 to December 2021. During her tenure as a Research Scholar, she taught several undergraduate courses, including “Computer Networks and Cisco Packet Tracer” at the 1st year level, “Database Management System” at the 2nd year level, and “Introduction to Web Technologies” also at the 2nd year level. Prior to her current position, Dr. Babbar worked as an Assistant Professor at the Chandigarh Group of Colleges, Landran (Mohali) from June 2016 to November 2017. Here, she taught courses such as “Digital Circuit and Logic Design”, “Software Engineering”, “System Analysis and Design (SAD)”, and “Oracle” at the 2nd year undergraduate level. Additionally, she supervised “Minor and Major Projects” at the 3rd year undergraduate level. She is also experienced in teaching “Workshop on Web Development” and “Java” at the 3rd year undergraduate level, as well as “Programming in C” at the 2nd year MBA (IT) level. Earlier in her career, Dr. Babbar held the position of Assistant Professor at the Aryans Group of Colleges, Chandigarh from August 2015 to November 2015. During this period, she taught “Information Technology” at the 1st year postgraduate level, “Digital Circuit and Logic Design” at the 2nd year undergraduate level, and “Programming in Java” at the 3rd year undergraduate level.

 

Research focus

Dr. Himanshi Babbar’s areas of expertise and research interests include Software Defined Networking, Internet of Things, Intrusion Detection Systems, and Deep Learning. These fields reflect her deep engagement with cutting-edge technologies and their applications, showcasing her commitment to advancing knowledge and innovation in these domains

Skills:

Dr. Himanshi Babbar possesses a strong technical skill set, including proficiency in programming languages such as C, C++, and Python. Her software skills include experience with development environments and tools like Eclipse, Turbo C++, Dev C++, Code-Blocks, ORACLE, NetBeans, and Mininet. She is adept at using various operating systems, including Windows 8, Windows 7, Windows XP, and Ubuntu 18.04 LTS. Additionally, Dr. Babbar is skilled in using Overleaf (LATEX) for document preparation, Origin for data analysis, and MS-Office Suite (Word, Excel, PowerPoint) for general office tasks.

Publication top notes

  • Security framework for internet-of-things-based software-defined networks using blockchain
    • Year: 2022
    • Journal: IEEE Internet of Things Journal
    • Authors: S Rani, H Babbar, G Srivastava, TR Gadekallu, G Dhiman
    • πŸ“…πŸ”’πŸŒ
  • An optimized approach of dynamic target nodes in wireless sensor network using bio inspired algorithms for maritime rescue
    • Year: 2022
    • Journal: IEEE Transactions on Intelligent Transportation Systems
    • Authors: S Rani, H Babbar, P Kaur, MD Alshehri, SH Shah
    • πŸ“…πŸš’πŸ”„
  • An efficient and lightweight deep learning model for human activity recognition using smartphones
    • Year: 2021
    • Journal: Sensors
    • Authors: Ankita, S Rani, H Babbar, S Coleman, A Singh, HM Aljahdali
    • πŸ“…πŸ“±πŸ§ 
  • Load balancing algorithm for migrating switches in software-defined vehicular networks
    • Year: 2021
    • Journal: Comput. Mater. Contin
    • Authors: H Babbar, S Rani, M Masud, S Verma, D Anand, N Jhanjhi
    • πŸ“…πŸš—πŸ”„
  • Energy‐Efficient Routing Protocol for Next‐Generation Application in the Internet of Things and Wireless Sensor Networks
    • Year: 2022
    • Journal: Wireless Communications and Mobile Computing
    • Authors: R Dogra, S Rani, H Babbar, D Krah
    • πŸ“…πŸ”‹πŸ“‘
  • Intelligent edge load migration in SDN-IIoT for smart healthcare
    • Year: 2022
    • Journal: IEEE Transactions on Industrial Informatics
    • Authors: H Babbar, S Rani, SA AlQahtani
    • πŸ“…πŸ₯πŸ”„
  • A genetic load balancing algorithm to improve the QoS metrics for software defined networking for multimedia applications
    • Year: 2022
    • Journal: Multimedia Tools and Applications
    • Authors: H Babbar, S Parthiban, G Radhakrishnan, S Rani
    • πŸ“…πŸŽ₯πŸ”„
  • Load balancing algorithm on the immense scale of internet of things in SDN for smart cities
    • Year: 2021
    • Journal: Sustainability
    • Authors: H Babbar, S Rani, D Gupta, HM Aljahdali, A Singh, F Al-Turjman
    • πŸ“…πŸ™οΈπŸ”„
  • Cloud based smart city services for industrial internet of things in software-defined networking
    • Year: 2021
    • Journal: Sustainability
    • Authors: H Babbar, S Rani, A Singh, M Abd-Elnaby, BJ Choi
    • πŸ“…β˜οΈπŸ™οΈ
  • Software-defined networking framework securing internet of things
    • Year: 2020
    • Journal: Integration of WSN and IoT for Smart Cities
    • Authors: H Babbar, S Rani
    • πŸ“…πŸ”’πŸ“‘

Prakhar Consul | Computer Science | Best Researcher Award

Published on by Global Scholar Awards

Prakhar Consul | Computer Science | Best Researcher Award

Mr Prakhar Consul, Bennett University, India

Prakhar Consul is an Assistant Professor and Ph.D. candidate at Bennett University, specializing in Internet-of-Things, Mobile Edge Computing, and Deep Reinforcement Learning. He holds an M.Tech. in Electronics and Communication from Sharda University and a B.Tech. from Shobhit University. With a robust teaching background in subjects like Microprocessors and Embedded Systems, his research focuses on computational offloading and resource allocation for UAV-assisted Mobile Edge Computing in 5G networks. Prakhar has taught at Dewan V S Institute, Neelkanth Group of Institutions, and I A M R Group of Institutions. πŸŽ“πŸ“‘πŸ€–πŸ“˜

Publication profile

google scholar

Education

Dr. Prakhar Consul is a Ph.D. candidate in Computer Science Engineering at Bennett University, India, expected to complete in Nov. 2024. Their thesis focuses on computational offloading and resource allocation in mobile edge computing using machine learning in 5G networks πŸ“‘. They hold an M.Tech in Electronics and Communication from Sharda University (2015) with a thesis on microstrip patch antennas πŸ“Ά. Dr. Prakhar Consul also has a B.Tech in Electronics and Communication from Shobhit University (2013) and completed their senior secondary education at J.A.S. Inter College 🏫. Their academic journey is marked by excellence and innovation in engineering and technology πŸ’‘.

Experience

Dr. Prakhar Consul served as an Assistant Professor in the Department of Electronics and Communication Engineering at Dewan V S Institute of Engineering and Technology (DVSIET), Meerut, India, from January 2020 to October 2021. Prior to this, they worked at Neelkanth Group of Institutions (NGI), Meerut, from August 2018 to January 2020 in the Department of Electronics and Electrical Engineering. From August 2015 to August 2018, they were part of the Department of Electronics and Communication Engineering at I A M R Group of Institutions, Meerut. Their extensive teaching experience highlights their dedication to education and engineering. πŸ“šπŸ”ŒπŸ‘¨β€πŸ«

Research focus

P. Consul’s research focuses on advancing wireless communication systems, with an emphasis on energy efficiency, security, and optimization in emerging technologies. His work includes developing innovative antenna designs, such as microstrip and U-slotted patch antennas, and enhancing energy-efficient schemes for mobile edge computing (MEC) using federated learning and reinforcement learning. He explores security in UAV-assisted systems, with solutions for secure computation and resource allocation in blockchain-assisted cyber-physical systems. His research also covers dual and triple band gap antennas and resource optimization strategies for digital twin-empowered UAV networks. πŸš€πŸ“‘πŸ”

Publication top notes

Triple band gap coupled microstrip U-slotted patch antenna using L-slot DGS for wireless applications

Federated learning based energy efficient scheme for MEC with NOMA underlaying UAV

Power allocation scheme based on DRL for CF massive MIMO network with UAV

Security reassessing in UAV-assisted cyber-physical systems based on federated learning

Deep reinforcement learning based energy consumption minimization for intelligent reflecting surfaces assisted D2D users underlaying UAV network

FLBCPS: federated learning based secured computation offloading in blockchain-assisted cyber-physical systems

A review of different vulnerabilities of security in a layered network

A hybrid secure resource allocation and trajectory optimization approach for mobile edge computing using federated learning based on WEB 3.0

A Hybrid Task Offloading and Resource Allocation Approach For Digital Twin-Empowered UAV-Assisted MEC Network Using Federated Reinforcement Learning For Future Wireless Network

Federated reinforcement learning based task offloading approach for MEC-assisted WBAN-enabled IoMT