Shalli Rani | Computer Science | Best Researcher Award

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Prof. Shalli Rani | Computer Science | Best Researcher Award

Professor | Chitkara University | India

Prof. Shalli Rani is a distinguished researcher in the fields of Internet of Things, Wireless Sensor Networks, Cloud Computing, and Machine Learning, with a prolific record of high-impact publications, books, patents, and editorial contributions. She has demonstrated exceptional leadership in guiding numerous PhD and ME students, fostering innovation and research excellence. Her work effectively bridges academia and industry through applied projects, including smart healthcare solutions, Industry 5.0 initiatives, and explainable AI systems. Recognized globally through invited talks, conference engagements, and editorial responsibilities in top journals, she has established herself as a thought leader in her domain. Her research contributions reflect both depth and breadth, combining theoretical rigor with practical relevance. Prof. Rani’s measurable research impact on Scopus is remarkable, with 4,400 citations, 311 documents, and an h-index of 34, highlighting her sustained influence and scholarly excellence in the international research community.

Profiles: Scopus | Google Scholar | ORCID

Featured Publications

1. S. Rani, R. Talwar, J. Malhotra, S. Ahmed, M. Sarkar, and H. Song, “A novel scheme for an energy efficient Internet of Things based on wireless sensor networks,” Sensors, vol. 15, no. 11, pp. 28603–28626, 2015.

2. S. Rani, S. H. Ahmed, and R. Rastogi, “Dynamic clustering approach based on wireless sensor networks genetic algorithm for IoT applications,” Wireless Networks, vol. 26, no. 4, pp. 2307–2316, 2020.

3. S. Bharany, S. Badotra, S. Sharma, S. Rani, M. Alazab, and R. H. Jhaveri, “Energy efficient fault tolerance techniques in green cloud computing: A systematic survey and taxonomy,” Sustainable Energy Technologies and Assessments, vol. 53, p. 102613, 2022.

4. G. S. Brar, S. Rani, V. Chopra, R. Malhotra, H. Song, and S. H. Ahmed, “Energy efficient direction-based PDORP routing protocol for WSN,” IEEE Access, vol. 4, pp. 3182–3194, 2016.

5. S. Rani, D. Koundal, M. F. Ijaz, M. Elhoseny, and M. I. Alghamdi, “An optimized framework for WSN routing in the context of Industry 4.0,” Sensors, vol. 21, no. 19, p. 6474, 2021.

Baha Ihnaini | Computer Science | Outstanding Contribution Award

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Dr. Baha Ihnaini | Computer Science | Outstanding Contribution Award

Assistant Professor at Wenzhou-Kean University, China

Dr. Baha Ihnaini is an accomplished academic and researcher in computer science with expertise spanning artificial intelligence, data science, machine learning, and natural language processing. His scholarly work has addressed significant challenges in sentiment analysis, medical diagnostics, disease prediction, and misinformation detection, with publications in respected journals and international conferences. Notably, he has contributed to developing Arabic lexicons for sentiment analysis, enhancing AI-driven healthcare solutions, and advancing transfer learning models for predictive analytics. Alongside his research, Dr. Ihnaini has demonstrated a strong commitment to teaching, covering a wide range of computer science courses and mentoring students in senior projects. His service on academic committees and involvement in curriculum development highlight his leadership and dedication to institutional growth. With a record of impactful research, effective teaching, and professional service, Dr. Ihnaini stands out as a valuable contributor to his field and a strong candidate for academic recognition.

Professional Profile 

Google Scholar | Scopus Profile | ORCID Profile 

Education

Dr. Baha Ihnaini holds a Ph.D. in Computer Science with a specialization in Data Science from Universiti Utara Malaysia, where his research focused on developing an expandable Arabic lexicon and sentiment analysis rules for social media text. He also earned a Master of Science in Management Information Systems from The Arab Academy for Banking and Financial Sciences, equipping him with a strong foundation in both technical and managerial aspects of information technology. His academic journey began with a Bachelor’s degree in Computer Engineering from Philadelphia University in Jordan, providing him with comprehensive knowledge of hardware, software, and systems engineering. This multidisciplinary educational background has enabled Dr. Ihnaini to integrate advanced computational methods with practical problem-solving approaches, particularly in the areas of machine learning, natural language processing, and data-driven applications. His academic credentials reflect a balance between rigorous technical expertise and applied research in emerging fields of computing.

Experience

Dr. Ihnaini has accumulated rich professional experience as an educator, researcher, and academic leader across several institutions. He currently serves as an Assistant Professor of Computer Science at Wenzhou-Kean University, where he teaches a broad range of courses, from foundational programming and systems to advanced research in computer science. His roles extend beyond teaching, as he actively contributes to academic committees focused on curriculum development, faculty hiring, and student support. Prior to this, he served as an Adjunct Professor at Al Ain University and BTEC Abu Dhabi, as well as a Lecturer at Al Khawarizmi International College, where he guided student projects and curriculum design. Earlier in his career, he worked as a Research Officer at Universiti Utara Malaysia’s InterNetWorks Research Lab, where he played a pivotal role in advancing sentiment analysis for Arabic text. Collectively, his experience reflects a strong commitment to research, teaching excellence, and academic service.

Research Focus

Dr. Ihnaini’s research focuses on artificial intelligence, machine learning, data science, and natural language processing, with an emphasis on solving real-world problems through intelligent systems. A significant part of his work has concentrated on Arabic sentiment analysis, where he developed innovative linguistic resources and computational models to improve text classification accuracy. His recent research extends to medical AI, including predictive modeling for diseases such as diabetic retinopathy, Alzheimer’s disease, and vitamin D deficiency, showcasing his ability to merge computer science with healthcare applications. He has also contributed to the advancement of fake news detection, stock market prediction using sentiment data, and multimodal semantic similarity. His interdisciplinary approach highlights the versatility of data-driven methods and their societal impact, from enhancing healthcare systems to improving digital communication analysis. Through these diverse but interconnected research directions, Dr. Ihnaini continues to contribute to both theoretical advancements and practical innovations in computer science.

Award and Honor

Dr. Ihnaini has earned recognition for his scholarly contributions through research publications in reputable international journals and conferences, with several works indexed in Scopus and well-regarded platforms. His achievements include developing novel computational methods for sentiment analysis, interdisciplinary research in healthcare prediction models, and the application of advanced machine learning techniques to real-world problems. His role as a key contributor to collaborative projects with international researchers further reflects the recognition of his expertise and the impact of his work. Beyond research, his commitment to education and service has been acknowledged within the institutions he has served, particularly through his involvement in curriculum innovation and student mentorship. While formal distinctions are highlighted through his publication record and conference participation, his career trajectory itself demonstrates consistent recognition as a capable scholar and educator. His growing research visibility and international collaborations continue to strengthen his candidacy for prestigious awards and honors.

Publication Top Notes

  • Title: A smart healthcare recommendation system for multidisciplinary diabetes patients with data fusion based on deep ensemble learning
    Authors: B Ihnaini, MA Khan, TA Khan, S Abbas, MS Daoud, M Ahmad, MA Khan
    Year: 2021
    Citations: 158

  • Title: Machine Learning Empowered Software Defect Prediction System
    Authors: MS Daoud, S Aftab, M Ahmad, MA Khan, A Iqbal, S Abbas, M Iqbal, B Ihnaini
    Year: 2022
    Citations: 37

  • Title: Stock trend prediction using sentiment analysis
    Authors: Q Xiao, B Ihnaini
    Year: 2023
    Citations: 35

  • Title: Joint channel and multi-user detection empowered with machine learning
    Authors: MS Daoud, A Fatima, WA Khan, MA Khan, S Abbas, B Ihnaini, M Ahmad
    Year: 2021
    Citations: 31

  • Title: Real-time shill bidding fraud detection empowered with fussed machine learning
    Authors: WUH Abidi, MS Daoud, B Ihnaini, MA Khan, T Alyas, A Fatima, M Ahmad
    Year: 2021
    Citations: 28

  • Title: Rider weed deep residual network-based incremental model for text classification using multidimensional features and MapReduce
    Authors: HB Abdalla, AM Ahmed, SRM Zeebaree, A Alkhayyat, B Ihnaini
    Year: 2022
    Citations: 18

  • Title: Presenting and evaluating scaled extreme programming process model
    Authors: M Ibrahim, S Aftab, M Ahmad, A Iqbal, BS Khan, M Iqbal, BNS Ihnaini
    Year: 2020
    Citations: 13

  • Title: Exploring the agile family: A survey
    Authors: M Ibrahim, S Aftab, B Bakhtawar, M Ahmad, A Iqbal, N Aziz, MS Javeid, B Ihnaini
    Year: 2020
    Citations: 12

  • Title: Predicting vitamin D deficiency using optimized random forest classifier
    Authors: A Alloubani, B Abuhaija, M Almatari, G Jaradat, B Ihnaini
    Year: 2024
    Citations: 9

  • Title: Lexicon-based sentiment analysis of Arabic tweets: A survey
    Authors: B Ihnaini, M Mahmuddin
    Year: 2018
    Citations: 9

  • Title: A Severity Grading Framework for Diabetic Retinopathy Detection using Transfer Learning
    Authors: S Akhtar, S Aftab, S Kousar, A Rehman, M Ahmad, AQ Saeed, B Ihnaini
    Year: 2024
    Citations: 8

  • Title: Improving the Quality of e-Commerce Service by Implementing Combination Models with Step-by-Step, Bottom-Up Approach
    Authors: BA Hemn, G Chengwei, B Ihnaini
    Year: 2021
    Citations: 6

  • Title: Sentiment analysis of Song Dynasty classical poetry using fine-tuned large language models: a study with LLMs
    Authors: B Ihnaini, W Sun, Y Cai, Z Xu, R Sangi
    Year: 2024
    Citations: 5

  • Title: A transfer learning based framework for diabetic retinopathy detection using data fusion
    Authors: S Akhtar, S Aftab, M Ahmad, B Ihnaini
    Year: 2024
    Citations: 4

  • Title: Semantic similarity on multimodal data: A comprehensive survey with applications
    Authors: B Ihnaini, B Abuhaija, EA Mills, M Mahmuddin
    Year: 2024
    Citations: 3

Conclusion

Dr. Baha Ihnaini’s publication record reflects a strong and steadily growing research trajectory across diverse yet interconnected fields of computer science, including artificial intelligence, data science, natural language processing, and medical informatics. His works demonstrate both theoretical depth and practical applications, ranging from healthcare prediction models and fraud detection to sentiment analysis and software engineering. The high citation impact of certain publications highlights the relevance and influence of his research in the academic community, while his more recent works indicate an expanding focus on interdisciplinary applications such as healthcare and cultural text analysis using advanced AI techniques. Collectively, his contributions showcase a balance of innovation, collaboration, and societal relevance, positioning him as a researcher whose work is not only academically significant but also impactful in addressing real-world challenges. This combination of influence, diversity, and practical value strengthens his candidacy for recognition through awards and honors.

Wenming Wang | Computer Science | Best Researcher Award

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Dr. Wenming Wang | Computer Science | Best Researcher Award

Dr. at Anqing Normal University, China

Dr. Wenming Wang is an esteemed scholar in the field of information security, currently serving as an associate professor at the School of Computer and Information, Anqing Normal University, China. With a strong academic background and a passion for cybersecurity, he has contributed significantly to research on secure communication and network protection. His expertise spans various domains, including IoT security, vehicular ad hoc networks, and cloud computing security. Dr. Wang is committed to advancing knowledge in these critical areas, helping to develop innovative solutions for modern cybersecurity challenges. Throughout his career, he has been actively engaged in both academia and research, striving to bridge the gap between theoretical advancements and practical applications. His dedication to fostering cybersecurity awareness and enhancing network security protocols has made him a respected figure in his field.

Professional Profile

Education

Dr. Wang obtained his Master of Science (M.S.) degree from Jinan University, Guangzhou, China, in 2014, where he built a strong foundation in information technology and security. Pursuing further academic excellence, he earned his Ph.D. in Information Security from Nanjing University of Posts and Telecommunications, Nanjing, China, in 2022. His doctoral research focused on advanced cybersecurity frameworks and encryption mechanisms, contributing to the development of innovative security solutions for emerging technologies. His academic journey reflects a deep commitment to continuous learning and research excellence, enabling him to address complex security challenges in the digital landscape. With a solid educational background and specialized training, Dr. Wang has established himself as a knowledgeable researcher in cybersecurity, equipping him with the skills and expertise required to tackle modern information security threats and vulnerabilities.

Professional Experience

Dr. Wenming Wang is currently an associate professor at the School of Computer and Information, Anqing Normal University, China. In this role, he is actively involved in teaching, mentoring students, and conducting cutting-edge research in the field of information security. Before joining Anqing Normal University, he gained extensive experience in cybersecurity research, focusing on network security, cryptography, and secure communication technologies. Throughout his career, he has collaborated with esteemed researchers and institutions to enhance cybersecurity measures across various domains. His role as an educator has allowed him to shape the next generation of cybersecurity professionals by imparting both theoretical knowledge and practical insights. Dr. Wang’s professional experience demonstrates his dedication to academic excellence and his commitment to advancing research in information security through collaboration and innovation.

Research Interests

Dr. Wang’s research primarily focuses on IoT security, vehicular ad hoc networks, and cloud computing security—three crucial areas in today’s rapidly evolving technological landscape. His work aims to develop robust security protocols that protect data integrity, confidentiality, and network resilience against cyber threats. In IoT security, he explores authentication and encryption techniques to safeguard smart devices from unauthorized access. His research in vehicular ad hoc networks emphasizes secure vehicle-to-vehicle communication to ensure safe and reliable transportation systems. Additionally, his studies on cloud computing security involve designing advanced cryptographic methods to enhance data privacy and prevent cyberattacks in cloud environments. His research contributions play a pivotal role in shaping the future of secure digital ecosystems by addressing critical vulnerabilities and proposing innovative security mechanisms.

Awards and Honors

Dr. Wang has received recognition for his contributions to cybersecurity research through various academic and professional accolades. While specific awards and honors are not listed, his work has likely been acknowledged through research grants, conference presentations, and journal publications. He has actively participated in national and international cybersecurity forums, presenting his findings and engaging with the global research community. His commitment to excellence has also earned him opportunities to collaborate with leading experts in the field. As he continues to expand his research impact, he is poised to achieve further recognition for his pioneering work in information security. His dedication to academic and research excellence positions him as a key figure in advancing cybersecurity innovations.

Conclusion

Dr. Wenming Wang appears to be a promising researcher with expertise in cybersecurity-related fields. However, based on the given information, his suitability for the Best Researcher Award depends on the depth of his research contributions, publication impact, and academic recognition. If he has high-impact publications, significant citations, or major research projects, he would be a strong candidate.

Publications Top Notes

  • Publication: Malicious Vehicle Detection Scheme Based on UAV and Vehicle Cooperative Authentication in Vehicular Networks

    • Author(s): W. Wang, Wenming; Z. Liu, Zhiquan; L. Xue, Lingyan; H. Huang, Haiping; N.R. Lavuri, Nageswara Rao

    • Journal: Computer Networks

    • Year: 2025

    • Citations: 0

  • Publication: A Cross-Domain Authentication Scheme for Vehicular Networks Based on Mobile Edge Computing

    • Author(s): G. Liu, Guijiang; H. Lu, Hao; W. Wang, Wenming; Z. Liu, Zhiquan; H. Huang, Haiping

    • Journal: IEEE Internet of Things Journal

    • Year: 2025

    • Citations: 0

 

Sun Park | Computer Science | Best Research Article Award

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Dr. Sun Park | Computer Science | Best Research Article Award

Research Associate Professor at, Gwangju Institute of Science and Technology, South Korea

Sun Park is a Research Associate Professor at the Graduate School of AI at Gwangju Institute of Science and Technology, a position held since 2013. Her research focuses on data mining, information retrieval, information summarization, convergent marine ICT, smart farming, and IoT-cloud & AI computing. Prior to this role, she served as a Research Professor at Mokpo National University’s Information Industry Research Institute from 2010 to 2013. She also worked as a Full-time Lecturer at Honam University from 2008 to 2010 and as an Adjunct Professor at Hanseo University from 2002 to 2007. Sun Park holds a Ph.D. in Computer Information Engineering from Inha University (2007), a Master’s degree in Information and Communication Engineering from Hannam University (2001), and a Bachelor’s degree in Computer Science from Jeonju University (1996). References are available upon request.

Publication Profile

Strengths for the Award

  1. Extensive Experience in Research and Teaching: Sun Park has over a decade of research and teaching experience, with key positions at prestigious institutions like the Gwangju Institute of Science and Technology, Mokpo National University, Honam University, and Hanseo University. This variety of roles highlights a significant breadth and depth of expertise in the field of Computer Science and Engineering.
  2. Specialized Research Focus: Their research areas, including Data Mining, Information Retrieval, Convergent Marine ICT, IoT-Cloud & AI Computing, and Smart Farm, align well with current and emerging technological trends. This suggests that Sun Park is contributing to forward-thinking, impactful research.
  3. AI and Converging Technologies: As a Research Associate Professor at the Graduate School of AI, Sun Park is in a prime position to lead interdisciplinary projects, bringing together fields like AI, IoT, and smart technologies. These areas are critical for innovation, making their work relevant for contemporary challenges.
  4. Strong Academic Background: Holding a Ph.D. in Computer Information Engineering and advanced degrees in Information and Communication Engineering, Sun Park’s academic credentials demonstrate a high level of expertise. The progression from a Bachelor’s to a Ph.D. showcases a long-standing commitment to the field.
  5. Institutional Impact: Serving in high-ranking academic roles implies that Sun Park has contributed to shaping research strategies, mentoring students, and advancing their institution’s academic reputation, which is a critical factor for awards that recognize leadership in research.

Areas for Improvement

  1. Lack of Specific Research Achievements: The provided profile does not detail significant publications, patents, or specific innovations. A more robust record of high-impact publications or citations would strengthen Sun Park’s candidacy for the Best Researcher Award. Highlighting specific projects or research grants won would also add weight.
  2. Global Collaboration and Visibility: While the candidate is clearly well-established in South Korea, a stronger record of international collaborations, keynote speeches, or participation in global conferences would further elevate their profile. Visibility in international research communities is often crucial for award considerations.
  3. Applied Outcomes or Industry Impact: While the research areas are impressive, the profile does not specify applied outcomes or how these research fields have impacted industries or society. Showcasing tangible applications of research (e.g., how IoT solutions have benefited smart farms or marine industries) would demonstrate real-world influence.

Education:

Sun Park holds a Ph.D. in Computer Information Engineering from Inha University, earned between 2002 and 2007, which forms the foundation of their advanced expertise in computer science. Prior to this, they completed a Master’s degree in Information and Communication Engineering at Hannam University from 1997 to 2001. This followed a Bachelor’s degree in Computer Science from Jeonju University, obtained between 1992 and 1996. This strong academic background, progressing from undergraduate to doctoral levels, demonstrates a deep and comprehensive education in computing and engineering disciplines.

Experience:

Sun Park has over two decades of academic and research experience, spanning various prestigious roles in South Korea. Currently serving as a Research Associate Professor at the Graduate School of AI at Gwangju Institute of Science and Technology, they focus on cutting-edge research in areas like Data Mining, Information Retrieval, Convergent Marine ICT, IoT-Cloud & AI Computing, and Smart Farm technologies. Previously, they held positions as a Research Professor at Mokpo National University and a Full-time Lecturer at Honam University. Sun Park’s academic journey, from earning a Ph.D. in Computer Information Engineering to holding multiple teaching and research roles, reflects a deep and broad expertise in computer science, with a strong commitment to innovation in AI and emerging technologies.

Research Focus:

Sun Park’s research focuses on several cutting-edge fields, including Data Mining, Information Retrieval, Information Summarization, Convergent Marine ICT, Smart Farming, and IoT-Cloud & AI Computing. This diverse range of interests demonstrates a commitment to advancing both theoretical and practical applications in technology. Their work bridges multiple domains, with a particular emphasis on integrating AI and IoT for innovative solutions in areas like agriculture and marine industries. By focusing on emerging technologies and their real-world implications, Sun Park’s research contributes to solving contemporary challenges in information management and intelligent systems.

Awards and Honors:

Sun Park’s awards and honors are not specifically listed in the provided profile. However, their notable academic positions, such as Research Associate Professor at the Graduate School of AI, Gwangju Institute of Science and Technology, and past roles at Mokpo National University and Honam University, suggest recognition of their expertise and leadership in their field. These roles reflect a high level of academic and research achievement, although further details on specific awards, honors, or recognitions would provide a clearer understanding of their accolades. Highlighting any formal awards or distinctions would strengthen their profile for the Best Researcher Award.

Publication Top Notes:

  • Design of Vessel Data Lakehouse with Big Data and AI Analysis Technology for Vessel Monitoring System
    • Authors: Park, S., Yang, C.-S., Kim, J.
    • Year: 2023
    • Citations: 6
  • Design and Implementation of Data Concentrator Unit supported with Multiple Synchronized Cameras for Object-Detection
    • Authors: Anvarjon, Y., Park, S., Kim, J.
    • Year: 2023
    • Citations: 0
  • Concept Design of Intelligent BoP Based on Slot-/Rack-type Fuel Cell for Integrated Management of Hydrogen Fuel Cells
    • Authors: Park, S., Chung, B.-J., Kim, J.
    • Year: 2023
    • Citations: 1
  • Correction to: Design of containerized marine knowledge system based on IoT-Cloud and LoRaWAN
    • Authors: Park, S., Ling, T.C., Cha, B.R., Kim, J.W.
    • Year: 2022
    • Citations: 1
  • Design of containerized marine knowledge system based on IoT-Cloud and LoRaWAN
    • Authors: Park, S., Ling, T.C., Cha, B.R., Kim, J.W.
    • Year: 2022
    • Citations: 3

Conclusion:

Sun Park’s extensive academic experience, specialized focus in key technological areas, and position within a prominent research institution make them a strong candidate for a research award. However, to be highly competitive for a Best Researcher Award, it would be beneficial for them to highlight specific high-impact research achievements, international collaborations, and real-world applications of their work. These additions would showcase a broader influence in both academic and industrial sectors, further solidifying their candidacy for this prestigious recognition.