Huda Alhajjaj | AI in Education | Editorial Board Member

Published on by Computer Scientists Awards

Editorial Board Member

Huda Alhajjaj
Affiliation University of Jordan
Country Jordan
Documents 15
Citations 45
h-index 5
Subject Area AI in Education
Event Computer Scientists Awards
ORCID 0000-0003-2535-4377

Huda Alhajjaj
University of Jordan

Huda Alhajjaj is an academic researcher affiliated with the University of Jordan, Jordan, whose research interests focus on artificial intelligence in education. Her scholarly profile is associated with the application of artificial intelligence and emerging digital technologies within educational contexts.

Abstract

Huda Alhajjaj is a researcher at the University of Jordan whose academic interests include artificial intelligence in education. Her research profile reflects engagement with the intersection of computational technologies and educational practice. The available scholarly record identifies 15 documents, 45 citations, and an h-index of 5. These indicators provide a quantitative description of her documented research activity and scholarly visibility.

Keywords

  • Artificial Intelligence
  • AI in Education
  • Educational Technology
  • Intelligent Learning
  • Digital Education

Introduction

Artificial intelligence is an increasingly important area of research in contemporary education. Applications include intelligent learning environments, educational analytics, adaptive systems, digital assistance, and technology-supported teaching. Research in this field examines how computational methods can complement educational practice while considering effectiveness, accessibility, and responsible implementation. Alhajjaj’s specialization in AI in education places her academic work within this interdisciplinary research area.

Research Profile

Alhajjaj is affiliated with the University of Jordan in Jordan. Her reported scholarly record includes 15 documents, 45 citations, and an h-index of 5. These indicators offer a concise overview of her documented publication and citation activity. Scholarly assessment, however, may also consider research methodology, originality, collaboration, publication venues, and the practical relevance of individual studies. [1]

Research Contributions

AI in education encompasses a broad range of research involving intelligent computational methods and educational applications. Relevant areas include personalized learning, educational data analysis, intelligent tutoring, automated support, and technology-enhanced learning. Alhajjaj’s research specialization contributes to this broader academic discussion by focusing on the relationship between artificial intelligence and educational environments.

Publications

The available academic profile records 15 documents associated with Huda Alhajjaj. These publications form part of her documented scholarly output and provide a basis for examining her research interests and contributions. Complete bibliographic information, including individual article titles, publication venues, and DOI identifiers, should be verified through the relevant scholarly records. [2]

Research Impact

The reported 45 citations and h-index of 5 provide quantitative indicators of citation activity associated with the researcher’s scholarly output. Citation measures can vary according to field, publication age, database coverage, and disciplinary citation practices. Consequently, these metrics are best interpreted together with qualitative assessment of research contributions and scholarly relevance.

Award Suitability

Alhajjaj’s academic affiliation, documented research activity, and specialization in AI in education provide a relevant scholarly profile for consideration in the context of the Computer Scientists Awards. Her subject area corresponds with an important and rapidly developing intersection of computer science, artificial intelligence, and education. Any formal award decision remains subject to the event’s applicable nomination, evaluation, and selection procedures. [3]

Conclusion

Huda Alhajjaj’s academic profile reflects research engagement in artificial intelligence in education at the University of Jordan. Her documented output of 15 publications, 45 citations, and an h-index of 5 provides measurable evidence of scholarly activity. Her research specialization places her within an interdisciplinary field that connects artificial intelligence, educational technology, and contemporary learning practices.

References

  1. ORCID. (n.d.). ORCID profile: Huda Alhajjaj.
    https://orcid.org/0000-0003-2535-4377
  2. Google Scholar. (n.d.). Huda Alhajjaj scholarly profile.
    https://scholar.google.com/citations?user=ELpp3X8AAAAJ&hl=en&oi=sra
  3. Computer Scientists Awards. (n.d.). Official website.
    https://computerscientists.net/

 

Ms. Yin ZiJuan | artificial intelligence | Best Researcher Award

Published on by Computer Scientists Awards

Ms. Yin ZiJuan | artificial intelligence | Best Researcher Award

Ms. Yin ZiJuan, graduate student, Shanghai University of Engineering Science, China.

Yin Zijuan is a dedicated graduate researcher at the School of Materials Science and Engineering, Shanghai University of Engineering Science. She has cultivated a unique interdisciplinary expertise that bridges materials science with artificial intelligence. Her notable work centers around intelligent surface defect detection using deep learning models. Yin gained international recognition for developing the BBW YOLO algorithm, which improves defect detection accuracy in aluminum profile manufacturing. With a passion for integrating AI into industrial applications, Yin exemplifies the new generation of scholars who are redefining engineering research through innovation, precision, and automation.

Publication Profile

Scopus

🎓 Education Background

Yin Zijuan is currently pursuing her graduate studies at the Shanghai University of Engineering Science, within the School of Materials Science and Engineering. Her academic focus lies in fusing materials engineering with advanced computational methods. During her studies, she developed specialized knowledge in deep learning, computer vision, and image processing as they relate to quality control in industrial materials. Her academic journey is marked by excellence, with her research earning publication in reputable international journals. Yin’s education reflects a strong foundation in both traditional materials science and cutting-edge AI methodologies.

🧪 Professional Experience

As a graduate researcher, Yin Zijuan has contributed to high-impact research projects focused on AI-driven defect detection in industrial materials. Her most distinguished project involved the development and implementation of the BBW YOLO algorithm, which blends Bidirectional Feature Pyramid Networks and attention mechanisms for enhanced image recognition. She has collaborated with institutions like Harbin Institute of Technology and participated in interdisciplinary studies that bridge academia and industry. Through her ongoing work, she aims to revolutionize quality assurance processes in manufacturing by deploying real-time and lightweight neural network systems.

🏆 Awards and Honors

Yin Zijuan has earned increasing recognition in the field of intelligent detection systems. Her research achievements culminated in a significant journal publication in Coatings, a Scopus and SCI-indexed journal, in 2025. This milestone established her as a rising scholar with contributions relevant to both academic and industrial domains. Her work on BBW YOLO has been lauded for its innovation, performance efficiency, and potential impact on industrial automation. Yin is also a nominee for prestigious awards including the Best Scholar Award, Outstanding Innovation Award, and Best Paper Award, all reflecting the excellence of her work.

🔬 Research Focus

Yin Zijuan’s research encompasses a wide spectrum of interdisciplinary themes including materials science, deep learning, and computer vision. Her primary focus is on developing intelligent detection algorithms for identifying surface defects in aluminum profiles. She has pioneered the BBW YOLO model, which integrates BiFPN and BiFormer attention mechanisms with a Wise-IoU v3 loss function. Her innovations improve defect detection accuracy while maintaining high processing speeds and model efficiency. Yin’s work supports the evolution of smart manufacturing and industrial automation, positioning her as a key contributor to the fusion of AI and engineering.

📌 Conclusion

Yin Zijuan exemplifies the future of smart materials research through her fusion of artificial intelligence and industrial materials science. Her work is not only academically rigorous but also practically relevant, addressing real-world problems in manufacturing. From algorithmic innovation to high-impact publication and inter-institutional collaboration, she has demonstrated exceptional promise as a research scholar. With her continued contributions, Yin is poised to lead transformative advancements in intelligent quality control systems. She stands as a worthy nominee for multiple academic honors and awards recognizing innovation, research excellence, and scholarly distinction.

📄 Top Publications Notes

  1. BBW YOLO: Intelligent Detection Algorithms for Aluminium Profile Material Surface Defects

  2. Thermal deformation behavior and microstructural evolution of the rapidly-solidified Al–Zn–Mg–Cu alloy in hot isostatic pressing state

 

 

 

 

 

Ms. ANKITA MANOHAR WALAWALKAR | Artificial Intelligence | Best Researcher Award

Published on by Computer Scientists Awards

Ms. ANKITA MANOHAR WALAWALKAR | Artificial Intelligence | Best Researcher Award

PhD, ASIA UNIVERSITY, TAIWAN

Ankita Manohar Walawalkar is an accomplished legal and academic professional from India, currently pursuing her Ph.D. in Business Administration at Asia University, Taiwan, with a strong focus on Artificial Intelligence, Corporate Governance, Human Resource Management, and Supply Chain. With a unique blend of legal expertise and international business experience, Ankita has spent over two decades navigating corporate procurement, translation, teaching, and research. Fluent in English, Hindi, and Chinese, she bridges cultural and linguistic gaps, making her a versatile contributor in academia and international business diplomacy. Her academic versatility, fieldwork experience, and multilingual proficiency make her a standout scholar and practitioner on global platforms.

Publication Profile

🎓 Education Background

Ankita is presently enrolled in a Ph.D. program in Business Administration at Asia University, Taiwan (2023–Present), focusing on interdisciplinary support areas such as AI, corporate governance, and HR. She holds a Master of Laws (LL.M.) in Corporate and Commercial Law from Amity University, Mumbai (2020–2021), where she deepened her expertise in IP, company law, and securities. Her foundational legal education was completed with a BLS-LLB from KES Jayantilal H. Patel Law College, University of Mumbai (2014–2020). Additionally, she completed a one-year Chinese Language Training at Zhengzhou University, China (2017–2018) under the prestigious Confucius Institute Scholarship.

💼 Professional Experience

Ankita’s dynamic professional career spans corporate sourcing and academia. From 2021 to 2023, she worked as a Sourcing Specialist at Algol Chemicals India Pvt. Ltd., New Delhi, specializing in Chinese supplier coordination, procurement, and logistics compliance. She has over five years of experience as a Freelance Interpreter and Translator, working with companies like VOXCO Pigments, Podar Enterprise, and Kohinoor Group, and participating in over 15 international exhibitions and conferences including the China-India Economic and Trade Conference. At Asia University, she serves as an EMI Teaching Assistant, TA for the Rural AI Bilingual Program, and works with the IC OIA office while volunteering at the INGO Research Centre. Her freelance work includes judicial interpretations, educational instruction for YCT/HSK levels, and market research projects for global clients.

🏆 Awards and Honors

Ankita was awarded the Confucius Institute Scholarship for a year-long language training program at Zhengzhou University, China (2017–2018), a testament to her dedication to language proficiency and cross-cultural studies. Her consistent participation in high-impact conferences and scholarly publications with global collaborators is a reflection of her ongoing academic recognition.

🔬 Research Focus

Ankita’s research interests are deeply rooted in AI Ethics, Corporate Governance, Human-AI Interaction, and Blockchain in HR, as reflected in her recent contributions to IGI Global book chapters and international conferences. She is actively involved in interdisciplinary explorations, combining law, ethics, and technology, with a notable focus on Human-AI collaboration in corporate decision-making, DEI challenges in hospital management, and the use of AI in education and language preservation.

📌 Conclusion

Ankita Manohar Walawalkar  stands at the unique intersection of law, language, and artificial intelligence, bringing over 20 years of diverse administrative, academic, and international experience to her work. Her contributions across education, corporate sourcing, and AI ethics research demonstrate her commitment to global impact and ethical innovation. As she continues her doctoral journey, her voice in the field of AI governance and multilingual education is becoming increasingly influential.

📝 Top Publication Notes

  1. Foundations of AI Ethics – 2024, IGI Global
    Cited by: 3 articles (as of 2024)
    Authors: Walawalkar, A. M., Moslehpour, M., Phattanaviroj, T., & Kumar, S.

  2. Utilization of Blockchain Technology to Manage Human Resources Data: Security Issues in Government Agencies – 2024, IGI Global
    Cited by: 2 articles
    Authors: Yati, P. P., & Walawalkar, A.

  3. Data Ethics and Privacy – 2024, IGI Global
    Cited by: 2 articles
    Authors: Phattanaviroj, T., Moslehpour, M., & Walawalkar, A. M.

  4. The Future of Ethical AI – 2024, IGI Global
    Cited by: 3 articles
    Authors: Firmansyah, G., Bansal, S., Walawalkar, A. M., Kumar, S., & Chattopadhyay, S.

  5. Investigating Human-AI Collaboration in Corporate Decision-Making for Sustainable Business Practices: An Extended UTAUT2 Model – 2025 (Upcoming), ICHESPAN Conference
    Status: Accepted, not yet cited
    Authors: Walawalkar, A. M., Moslehpour, M., Gupta, V., Rizaldy, H.

Dr. Zeynep Ilkilic Aytac | Artificial Intelligence | Best Researcher Award

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Dr. Zeynep Ilkilic Aytac | Artificial Intelligence | Best Researcher Award

Dr Lecturer, Ondokuzmayıs University, Turkey

Dr. Zeynep Ilkilic Aytac is a dynamic and innovative academician serving as a Lecturer at Ondokuz Mayıs University, Yeşilyurt Demir Çelik Vocational School, Department of Mechatronics 🏫. With over eight years of teaching experience, she has contributed significantly to interdisciplinary research that merges mechatronics, artificial intelligence 🤖, and sustainable technologies 🌱. Her strong academic foundation and passion for practical innovation enable her to mentor engineering students while advancing the frontiers of medical diagnostics and control systems. She is widely recognized for her work in MEMS gyroscope control, CNN-based cancer detection, and emission modeling using AI.

Publication Profile

🎓 Education Background

Dr. Aytac earned her BSc, MSc, and PhD degrees in Mechatronics Engineering from Fırat University, Turkey . Her academic journey showcases a strong foundation in mechanical-electrical integration, AI-driven design, and intelligent control systems. Her doctoral research focused on developing robust control strategies for MEMS gyroscopes, laying the groundwork for her multifaceted research career.

💼 Professional Experience

Currently a Lecturer at Ondokuz Mayıs University, Dr. Aytac brings over eight years of higher education teaching and project supervision experience. She has led various academic initiatives and research projects that combine engineering principles with AI and sustainability 🌐. Her interdisciplinary projects have strengthened both academic and industry collaborations, reflecting her commitment to applied research and impactful innovation.

🏅 Awards and Honors

Dr. Aytac has gained recognition for her research through publication in reputable international journals and conference proceedings 🏆. Although specific awards are not listed, her extensive interdisciplinary contributions and active role in innovation-driven education suggest an academic career marked by peer respect and institutional acknowledgment.

🔬 Research Focus

Her research interests lie in the robust control of MEMS gyroscopes, artificial intelligence in medical imaging 🧠, and emission prediction from internal combustion systems using neural networks. She has also focused on CNN-based thyroid cancer detection, leveraging hybrid metaheuristic optimization algorithms like COOT, GWO, PSO, and CMA-ES. Her contributions uniquely combine mechatronics, control theory, deep learning, and sustainability for real-world applications across engineering and healthcare.

🧩 Conclusion

Dr. Zeynep Ilkilic Aytac exemplifies the spirit of modern engineering innovation—bridging theoretical knowledge with hands-on impact. Her work continues to shape the convergence of control systems, AI, and biomedical diagnostics, enriching both academic fields and practical industries 🔧🧬. Through dedicated teaching, collaborative research, and a commitment to sustainable technology, she inspires the next generation of engineers and scientists.

📚 Top Publications 

AI-Based Emission Prediction Using Artificial Neural Networks Optimized by CMA-ES Algorithm.
Journal: Energy Reports, Year: 2022
Cited by: 24 articles

Robust Control of MEMS Gyroscopes Using Adaptive Sliding Mode Techniques.
Journal: Microsystem Technologies, Year: 2021
Cited by: 17 articles

Deep CNN Optimization for Thyroid Cancer Detection Using GWO and PSO.
Journal: Sensors, Year: 2023
Cited by: 12 articles

Hybrid AI Approaches in Digital Pathology: A CNN-Based Study.
Journal: IEEE Access, Year: 2022
Cited by: 9 articles

 Metaheuristic Optimization in CNNs for Histopathological Image Classification.
Journal: Expert Systems with Applications, Year: 2023
Cited by: 7 articles