Muhammad Firoz Mridha | Machine Learning | Best Researcher Award

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Prof. Dr. Muhammad Firoz Mridha | Machine Learning | Best Researcher Award

Professor | American International University | Bangladesh

Prof. Dr. Muhammad Firoz Mridha, a researcher at the American International University–Bangladesh (AIUB), has established a strong scholarly profile in computer science with notable contributions to machine learning, data analytics, cybersecurity, IoT, and applied artificial intelligence. With 319 publications, over 4,629 citations, and an h-index of 33, his work demonstrates sustained academic productivity and global research impact. His studies often address practical and emerging challenges—such as intelligent decision-support systems, secure digital infrastructures, and data-driven solutions for healthcare and smart environments—positioning his contributions at the intersection of theoretical advancement and real-world application. Collaboration is a defining feature of his career, reflected in partnerships with 575 co-authors, enabling multidisciplinary knowledge exchange and strengthening international research networks. His work has supported technological development, digital inclusion, and innovation-oriented problem-solving, particularly in contexts where data-centric technologies can improve societal outcomes.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Mridha, M. F., Keya, A. J., Hamid, M. A., Monowar, M. M., & Rahman, M. S. (2021). A comprehensive review on fake news detection with deep learning. IEEE Access, 9, 156151–156170.

Cited by: 297

2. Mridha, M. F., Das, S. C., Kabir, M. M., Lima, A. A., Islam, M. R., & Watanobe, Y. (2021). Brain–computer interface: Advancement and challenges. Sensors, 21(17), 5746.

Cited by: 296

3. Jim, J. R., Talukder, M. A. R., Malakar, P., Kabir, M. M., Nur, K., & Mridha, M. F. (2024). Recent advancements and challenges of NLP-based sentiment analysis: A state-of-the-art review. Natural Language Processing Journal, 6, 100059.

Cited by: 271

4. Rayed, M. E., Islam, S. M. S., Niha, S. I., Jim, J. R., Kabir, M. M., & Mridha, M. F. (2024). Deep learning for medical image segmentation: State-of-the-art advancements and challenges. Informatics in Medicine Unlocked, 47, 101504.

Cited by: 227

5. Mridha, M. F., Lima, A. A., Nur, K., Das, S. C., Hasan, M., & Kabir, M. M. (2021). A survey of automatic text summarization: Progress, process and challenges. IEEE Access, 9, 156043–156070.

Cited by: 197

Prof. Dr. Muhammad Firoz Mridha’s research advances data-driven intelligence and secure digital systems, contributing to global technological innovation and societal problem-solving. His work supports scalable, real-world applications—particularly in developing regions—promoting inclusive, ethical, and sustainable digital transformation.

Mahmoud Iskandarani | AI | Editorial Board Member

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Prof. Mahmoud Iskandarani | AI | Editorial Board Member

Professor | Al-Ahliyya Amman University | Jordan

Prof. Mahmoud Zaki Iskandarani’s research focuses on advancing wireless communication systems with specialization in wireless sensor networks (WSNs), intelligent reflecting surfaces (IRS), robotic communication platforms, adaptive beamforming techniques, and electromagnetic field modeling. With 84 publications, 167 citations, 5 h-index his scholarly output reflects sustained productivity and growing global recognition. His recent works address energy-efficient communication for robotic WSNs, SINR enhancement through adaptive IRS design, hybrid beamforming using Gaussian interpolation, and analytical–numerical modeling supported by neural predictors, demonstrating strong integration of computational intelligence with communication engineering. He has also contributed to transportation and mobility research through studies on BRT system impacts on congestion and safety, highlighting his capacity for multidisciplinary problem-solving. Collaborating with 11 co-authors across diverse domains, he publishes in reputable international journals such as IEEE Access, Journal of Communications, Journal of Robotics, and Cogent Engineering, reinforcing the breadth and relevance of his contributions. Collectively, his research advances theoretical models and practical frameworks that improve spectral efficiency, path-loss prediction accuracy, energy optimization, and network reliability in emerging 6G-oriented and autonomous systems, generating technological and societal value across communication, robotics, and smart mobility sectors.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Gardner, J. W., Iskandarani, M. Z., & Bott, B. (1992). Effect of electrode geometry on gas sensitivity of lead phthalocyanine thin films. Sensors and Actuators B: Chemical, 9(2), 133–142.

Cited by: 63

2. Iskandarani, M. Z. (2008). Effect of information and communication technologies (ICT) on non-industrial countries—Digital divide model. Journal of Computer Science, 4(4), 315.

Cited by: 41

3. Shilbayeh, N. F., & Iskandarani, M. Z. (2004). Quality control of coffee using an electronic nose system. American Journal of Applied Sciences, 1(2), 129–135.

Cited by: 41

4. Iskandarani, M. Z. (2025). Effect of Intelligent Reflecting Surface on WSN Communication with Access Points Configuration. IEEE Access, 13, 13380–13394.

Cited by: 29

5. Iskandarani, M. Z. (2025). Energy and path loss analysis of wireless sensor networks on a robotic body (WS Robotic). Bulletin of Electrical Engineering and Informatics, 14(3), 1794–1807.

Cited by: 25

Prof. Mahmoud Zaki Iskandarani’s work advances the performance, adaptability, and intelligence of wireless communication systems, contributing to the foundations of future 6G networks and autonomous robotic platforms. His research supports societal and industrial innovation by enabling more efficient connectivity, improved mobility systems, and smarter technological infrastructures worldwide.

Amirhossein Ghasemi Abyaneh | Machine Learning | Best Researcher Award

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Mr. Amirhossein Ghasemi Abyaneh | Machine Learning | Best Researcher Award

Researcher | Kharazmi University | Iran

Mr. Amirhossein Ghasemi Abyaneh is an emerging scholar in the field of artificial intelligence applications in sustainable supply chains, affiliated with Kharazmi University, Tehran, Iran. His academic endeavors focus on integrating advanced data analytics, optimization techniques, and machine learning frameworks to enhance decision-making, efficiency, and sustainability across complex supply chain networks. With 3 published research papers and an h-index of 1, Mr. Abyaneh has begun establishing a scholarly footprint that bridges technology-driven innovation with environmental and operational resilience. His work, including the open-access article “An Analytical Review of Artificial Intelligence Applications in Sustainable Supply Chains” (2025, Supply Chain Analytics), provides critical insights into the evolving intersection of AI and sustainability, emphasizing how digital intelligence can optimize resource utilization, reduce carbon footprints, and strengthen circular economy practices. Having received citations from international scholars, he actively contributes to the global academic dialogue on sustainable logistics, smart manufacturing, and responsible innovation. Mr. Abyaneh’s collaborative research network includes seven co-authors from diverse academic and institutional backgrounds, reflecting a strong interdisciplinary approach that combines engineering, data science, and environmental management. His studies aim to foster both theoretical advancement and practical applicability, offering valuable implications for policymakers, corporations, and researchers seeking to transition toward greener, data-driven supply chains. Beyond academic impact, his contributions align with global sustainability goals, promoting knowledge transfer, digital equity, and responsible AI adoption for societal benefit.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Sharbati, A., Movahed, A. B., Abyaneh, A. G., & Rahmanian, F. (2025). Risk assessment of healthcare systems using the FMEA method: Medication management process. Journal of Future Digital Optimization, 1(1), 71–85.
Cited by: 4

2. Abyaneh, A. G., Movahed, A. B., Abyari, A., Nodehfarahani, A., & Khakbazan, M. (2025). Evaluating the RFID technology in Costco Company: A focus on logistics and supply chain management. Applied Innovations in Industrial Management, 5(2), 34–51.
Cited by: 2

3. Movahed, A. B., Abyaneh, A. G., Khakbazan, M., & Movahed, A. B. (2025). Smart economy cybersecurity: AI-driven risk management in digital markets. In Dynamic and Safe Economy in the Age of Smart Technologies (pp. 49–72).
Cited by: 2

4. Abyaneh, A. G., Ghanbari, H., Mohammadi, E., Amirsahami, A., & Khakbazan, M. (2025). An analytical review of artificial intelligence applications in sustainable supply chains. Supply Chain Analytics, 100173.
Cited by: 1

5. Abyaneh, A. G., Khakbazan, M., & Movahed, A. B. (2026). Artificial intelligence in digital marketing: Trends, challenges, and strategic opportunities. In Improving Consumer Engagement in Digital Marketing Through Cognitive AI (pp. 225–260)

Mr. Amirhossein Ghasemi Abyaneh envisions a future where artificial intelligence empowers sustainable industrial transformation, enabling supply chains to become more adaptive, transparent, and environmentally responsible. His research advances the integration of smart analytics and sustainability principles, fostering innovation that supports global climate resilience and ethical technological progress.

Ushba Rasool | Generative AI | Best Researcher Award

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Dr. Ushba Rasool | Generative AI | Best Researcher Award

Research Instructor | Zhengzhou University | China

Dr. Ushba Rasool, affiliated with Zhengzhou University, China, is a rising researcher specializing in educational psychology, digital pedagogy, and artificial intelligence (AI) in education. With 11 publications, 68 citations, and an h-index of 5, her work integrates theoretical frameworks such as UTAUT (Unified Theory of Acceptance and Use of Technology) and TPACK (Technological Pedagogical Content Knowledge) to investigate teachers’ and students’ perceptions, attitudes, and adoption behaviors toward emerging educational technologies. Her recent publication in Acta Psychologica (2025), “Perceptions of Generative AI in Teaching and Learning,” highlights her innovative approach in merging psychological insights with technology acceptance models to explore the transformative potential of generative AI in learning environments. Through collaborations with 18 co-authors across international institutions, Dr. Rasool contributes to advancing global understanding of digital transformation in education, addressing key issues of AI ethics, digital literacy, and pedagogical innovation. Her research provides valuable implications for educational policy, technology integration strategies, and the enhancement of learner engagement, thus creating meaningful social and academic impact in the digital age.

Profiles: Scopus | Google Scholar

Featured Publications

1. Rasool, U., Qian, J., & Aslam, M. Z. (2023). An investigation of foreign language writing anxiety and its reasons among pre-service EFL teachers in Pakistan. Frontiers in Psychology, 13, 947867. 
Cited by: 64

2. Barzani, S. H. H. (2022). The effects of online supervisory feedback on student-supervisor communications during the COVID-19. European Journal of Educational Research, 11(3), 1569–1579. 
Cited by: 31

3. Barzani, S. H. H. (2021). Teachers and students’ perceptions towards online ESL classrooms during COVID-19: An empirical study in North Cyprus. The Journal of Asia TEFL, 18(4), 1423–1431. 
Cited by: 21

4. Rasool, U., Mahmood, R., Aslam, M. Z., Barzani, S. H. H., & Qian, J. (2023). Perceptions and preferences of senior high school students about written corrective feedback in Pakistan. SAGE Open, 13(3), 21582440231187612. 
Cited by: 17

5. Rasool, U., Aslam, M. Z., Mahmood, R., Barzani, S. H. H., & Qian, J. (2023). Pre-service EFL teachers’ perceptions of foreign language writing anxiety and some associated factors. Heliyon, 9(2), e13705. 
Cited by: 15

Dr. Ushba Rasool’s research fosters responsible and inclusive integration of generative AI in education, driving innovation in digital pedagogy and shaping global educational practices that empower both teachers and learners for a technologically adaptive future.

Tianyuan Liu | Machine Learning | Best Researcher Award

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Assoc. Prof. Dr. Tianyuan Liu | Machine Learning | Best Researcher Award

Master’s Supervisor | Donghua University | China

Assoc. Prof. Dr. Tianyuan Liu, affiliated with Donghua University, Shanghai, China, is a distinguished researcher specializing in industrial intelligence, human-centric manufacturing, and vision-based quality inspection. With 43 publications, 1,103 citations, and an h-index of 17, Dr. Liu’s work reflects significant academic impact and steady scholarly growth in intelligent industrial systems. His research integrates cognitive computing, deep learning, and large language models to enhance manufacturing precision, reliability, and adaptability. Notably, his 2025 article “Analysis of causes of welding defects in bridge weathering steel based on large language models” in the Journal of Industrial Information Integration demonstrates his pioneering approach to applying AI-driven diagnostic systems in structural materials engineering. Another major contribution, “Causal deep learning for explainable vision-based quality inspection under visual interference” published in Journal of Intelligent Manufacturing, advances explainable AI (XAI) frameworks for real-time industrial inspection, ensuring transparency and accuracy in automated decision-making. His review, “Towards cognition-augmented human-centric assembly: A visual computation perspective”, underscores his vision for augmenting human intelligence with computational cognition to achieve collaborative, efficient, and sustainable manufacturing systems. Furthermore, his book chapter “Industrial Intelligence: Methods and Applications” provides a comprehensive view of the synergy between AI and industrial processes, shaping the academic and applied discourse in smart factories. Assoc. Prof. Dr. Liu’s contributions collectively enhance the fusion of AI, cognition, and industrial engineering, driving forward the next generation of intelligent, explainable, and human-oriented manufacturing ecosystems.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Zhang, R., Lv, Q., Li, J., Bao, J., Liu, T., & Liu, S. (2022). A reinforcement learning method for human-robot collaboration in assembly tasks. Robotics and Computer-Integrated Manufacturing, 73, 102227.
Cited by: 182.

2. Zhou, B., Bao, J., Li, J., Lu, Y., Liu, T., & Zhang, Q. (2021). A novel knowledge graph-based optimization approach for resource allocation in discrete manufacturing workshops. Robotics and Computer-Integrated Manufacturing, 71, 102160.
Cited by: 152.

3. Zhou, B., Shen, X., Lu, Y., Li, X., Hua, B., Liu, T., & Bao, J. (2023). Semantic-aware event link reasoning over industrial knowledge graph embedding time series data. International Journal of Production Research, 61(12), 4117–4134.
Cited by: 123.

4. Zhou, B., Li, X., Liu, T., Xu, K., Liu, W., & Bao, J. (2024). CausalKGPT: Industrial structure causal knowledge-enhanced large language model for cause analysis of quality problems in aerospace product manufacturing. Advanced Engineering Informatics, 59, 102333.
Cited by: 114.

5. Liu, T., Bao, J., Wang, J., & Zhang, Y. (2018). A hybrid CNN–LSTM algorithm for online defect recognition of CO₂ welding. Sensors, 18(12), 4369.
Cited by: 105.

Assoc. Prof. Dr. Tianyuan Liu’s research bridges artificial intelligence and industrial engineering, advancing smart, explainable, and human-centric manufacturing solutions that empower global industry transformation.

Minoru Sasaki | Artificial Intelligence | Best Researcher Award

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Prof. Dr. Minoru Sasaki | Artificial Intelligence | Best Researcher Award

Organizing Committee | Gifu University | Japan

Prof. Dr. Minoru Sasaki, a distinguished Emeritus Professor at Gifu University, has made significant contributions to the fields of mechanical engineering, control systems, and mechatronics throughout his academic and professional career. With a Ph.D. in Mechanical Engineering from Tohoku University (1985), he has held various academic positions in Japan and internationally, including visiting professorships at UCLA, Georgia Institute of Technology, and King Mongkut’s University of Technology Thonburi. He has also served in numerous leadership roles at Gifu University, such as Department Chair, Assistant President, and Director of the Career Center. His professional affiliations include IEEE Life Senior Member, ASME, JSME, SICE (Fellow), RSJ, JSASS, and others. He has actively contributed to global academic and research communities through editorial roles in prestigious journals and program committees of international conferences. His involvement extends to advisory roles and leadership positions within key engineering societies in Japan and abroad. A prolific researcher, Dr. Sasaki has authored 202 publications, which have been cited by 966, reflecting a strong academic impact with an h-index of 14. These metrics highlight the depth and relevance of his research in intelligent mechanical systems and applied electromagnetics.

Profiles: Scopus | Google Scholar | ORCID

Featured Publications

1. Taheri, S. M., Matsushita, K., & Sasaki, M. (2017). Virtual reality driving simulation for measuring driver behavior and characteristics. Journal of Transportation Technologies, 7(02), 123.
Cited by 84.

2. Takayama, K., & Sasaki, M. (1983). Effects of radius of curvature and initial angle on the shock transition over concave and convex walls. Report of the Institute of High Speed Mechanics, 46, 1–30.
Cited by 66.

3. Yoshida, T., Sasaki, M., Ikeda, K., Mochizuki, M., Nogami, Y., & Inokuchi, K. (2002). Prediction of coal liquefaction reactivity by solid state 13C NMR spectral data. Fuel, 81(11-12), 1533–1539.
Cited by 64.

4. Endo, T., Sasaki, M., Matsuno, F., & Jia, Y. (2016). Contact-force control of a flexible Timoshenko arm in rigid/soft environment. IEEE Transactions on Automatic Control, 62(5), 2546–2553.
Cited by 61.

5. Takeda, K., Sasaki, M., Kieda, N., Katayama, K., Kako, T., Hashimoto, K., … (2001). Preparation of transparent super-hydrophobic polymer film with brightness enhancement property. Journal of Materials Science Letters, 20(23), 2131–2133.
Cited by 56.

Faten AlQaifi | Artificial Intelligence | Best Researcher Award

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Dr. Faten AlQaifi | Artificial Intelligence | Best Researcher Award

Atilim University, Turkey.

Dr. Faten Musaed Alqaifi is a multidisciplinary researcher currently pursuing her Master’s in Healthcare Management at Atılım University, Turkey. She brings a unique blend of expertise in dental surgery, healthcare management, and artificial intelligence, having earned her MBA in Healthcare Management from UTM, Malaysia. With academic excellence reflected in her top CGPAs, she has contributed to both clinical and psychosocial research domains. Her recent studies explore AI’s role in improving oral healthcare outcomes and the psychological dimensions of international student life. She has worked as a general dentist, educator, and volunteer in diverse cultural settings, underscoring her global adaptability and social commitment. Fluent in Arabic, English, and intermediate Turkish, Dr. Alqaifi exemplifies the qualities of a globally engaged researcher.

🌐Author Profiles

Strengths for the Award

  1. Interdisciplinary Research in Healthcare and AI
    Faten Alqaifi has shown a strong interdisciplinary approach, particularly in integrating artificial intelligence into healthcare systems. Her 2024 publication titled “Artificial intelligence’s impact on oral healthcare in terms of clinical outcomes: a bibliometric analysis” reflects a forward-thinking research agenda. By analyzing AI’s role in improving clinical outcomes, she contributes meaningfully to a high-impact and emerging area in health sciences and management.

  2. Empirical Work in Mental Health and Social Integration
    Her 2025 paper, “International students’ adaptation in Ankara: The mediating roles of anxiety and self-esteem”, published in the International Journal of Intercultural Relations, indicates her engagement with global psychological and sociocultural issues. This work not only highlights her concern for vulnerable populations but also showcases the use of rigorous methodologies in behavioral and intercultural research.

  3. Diverse Experience and Multilingual Skills
    Faten has a well-rounded professional background as a dentist, academic tutor, volunteer, and general manager. She speaks Arabic natively and is proficient in English and Turkish, enabling her to conduct research and collaboration across regions. Her use of advanced research tools (e.g., SPSS, SmartPLS, bibliometric software) further enhances her research capacity.

🔹 Education 

Dr. Alqaifi holds a Bachelor’s in Dental Surgery from the Yemeni University of Science and Technology, where she ranked fifth in her class. She earned her first Master’s degree—an MBA in Healthcare Management—from Universiti Teknologi Malaysia (UTM) with a stellar GPA of 3.94/4. Building on her academic and clinical background, she is now completing a second Master’s in Healthcare Management at Atılım University, Turkey, where she maintains a GPA of 3.93/4. Her ongoing thesis investigates the adoption of artificial intelligence in dentistry, combining technology, healthcare policy, and clinical practice. This educational trajectory highlights her commitment to interdisciplinary learning and research excellence.

🔹 Research Focus on Artificial Intelligence

Dr. Faten Alqaifi’s research lies at the intersection of healthcare innovation, artificial intelligence, and behavioral science. Her ongoing thesis on AI integration in dentistry demonstrates a forward-looking approach to digital transformation in healthcare. Her research agenda emphasizes both technological effectiveness and human-centered outcomes, as evidenced by her bibliometric analysis on AI’s clinical impact in oral healthcare. Simultaneously, she investigates psychological dimensions of social adaptation, particularly anxiety and self-esteem among international students—adding depth to her interdisciplinary reach. She is proficient in tools like SPSS, SmartPLS, and bibliometric analysis platforms, enabling her to conduct statistically robust, data-driven research. Faten’s aim is to bridge the digital and human aspects of healthcare policy and practice.

📚 Publication Top Notes

1. International Students’ Adaptation in Ankara: The Mediating Roles of Anxiety and Self-Esteem

Author: Faten Alqaifi
Journal: International Journal of Intercultural Relations, Vol. 108, Article 102249, 2025
Summary:
This study explores the psychological adjustment process among international students in Ankara, focusing on the mediating impact of anxiety and self-esteem on their adaptation levels. Using structural equation modeling, Alqaifi identifies critical pathways by which mental health factors influence sociocultural integration. The research provides insights for universities and policymakers aiming to improve the student experience in multicultural settings.

2. Artificial Intelligence’s Impact on Oral Healthcare in Terms of Clinical Outcomes: A Bibliometric Analysis

Authors: Faten Alqaifi, D. Tengilimoglu, I. Arslan Aras
Journal: Journal of Health Organization and Management, 2024
Summary:
This bibliometric study investigates global research trends on AI applications in oral healthcare. Analyzing data from Scopus and Web of Science, the authors assess publication patterns, key contributors, emerging keywords, and citation landscapes. The study concludes that AI is increasingly driving diagnostic precision, treatment planning, and clinical outcome optimization in dentistry. It positions AI as a transformative force and sets the foundation for future strategic investments in digital dentistry.

Conclusion

Dr. Faten Musaed Alqaifi shows strong potential for recognition as an emerging interdisciplinary researcher in healthcare, AI, and social sciences. Her academic excellence, early contributions in high-relevance areas, and diverse experience make her a promising candidate for the Best Researcher Award. However, to fully meet the expectations of this award at a global competitive level, she should aim to expand her publication portfolio, lead independent research projects, and pursue collaborative or funded initiatives. With her current trajectory and dedication, she is on a strong path to achieving these milestones.