Dayu Jia | Big Data Management | Best Researcher Award

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Mr. Dayu Jia | Big Data Management | Best Researcher Award

Associate Professor | Liaoning University | China

Dr. Jia Dayu is an Associate Professor and Master’s Supervisor at the School of Information Science, Liaoning University. He completed his Ph.D. in Computer Science at Northeastern University under the guidance of Prof. Wang Guoren and further gained international experience as a joint Ph.D. student at the National University of Singapore under Prof. Ooi Beng Chin. He also worked as a postdoctoral fellow at the School of Information Science and Engineering, Northeastern University. Dr. Jia has been actively involved in national, provincial, and ministerial research projects and has collaborated on international research initiatives. His research focuses on big data management, blockchain data analysis, and artificial intelligence, with expertise in scalable storage, secure data retrieval, and privacy-preserving techniques. He has published 21 high-quality papers in reputed journals and conferences, including Q1 journals such as Advanced Materials and Light: Science & Applications, and has served as the first or corresponding author on 12 publications in prestigious venues like JCST, WWW, and Software Journal. Dr. Jia has also been granted 13 national invention patents, demonstrating his innovative contributions, and has hosted or participated in six funded research projects. His skills include blockchain architecture design, data analytics, AI-driven optimization, and secure distributed systems. His work has earned recognition with 176 citations by 14 documents and an h-index of 5, reflecting the impact and relevance of his research in the academic community.

Profile : Scopus 

Featured Publication

1. Jia, D., Hu, Y., Huang, M., Zhang, J., He, G., Xu, S., Liu, S., & Wang, X. (2025). Security risks and solutions of concurrent PBFT. Expert Systems with Applications, 294, 128737.

Jun Peng | Big Data Analysis | Best Researcher Award

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Prof. Jun Peng | Big Data Analysis | Best Researcher Award

Professor | Ningbo University | China

Prof. Jun Peng is a distinguished scholar in the field of educational technology with expertise in big data in education, artificial intelligence in learning, blended learning, and curriculum design. He earned his PhD in Education from the University of Hong Kong and has built a strong academic career through teaching, research, and international collaborations. Currently serving as a professor and doctoral supervisor at Ningbo University, he has also contributed to the University of Hong Kong and the City University of Macau in research and teaching capacities. His professional experience includes leading several funded projects across China and Macau, with a focus on AI integration in education and innovative digital learning models. His research interests span online learning environments, project-based education, and sustainable approaches to technology-enhanced learning, reflected in numerous publications in leading SSCI, SCI, and Scopus-indexed journals such as Computers & Education, Education and Information Technologies, and Sustainability. Recognized with multiple commendations for research excellence, he has also received awards for educational innovation and course design. Prof. Peng is active in academic service as an editorial board member, peer reviewer for reputed journals, and keynote speaker at international conferences. His research skills include quantitative and qualitative analysis, big data applications, machine learning for education, and curriculum development. With a proven record of impactful research, leadership, and mentoring, he continues to advance the field of educational technology while contributing to the global academic community.

Profile: ORCID

Featured Publications

1.Shu, X., Peng, J., & Wang, G. (2023). Deciding alone or with others: Employment anxiety and social distance predict intuitiveness in career decision making. International Journal of Environmental Research and Public Health, 20(2), 1484.
2. Su, B., & Peng, J. (2023). Sentiment analysis of comment texts on online courses based on hierarchical attention mechanism. Applied Sciences, 13(7), 4204.
3. Zhou, J., Ran, F., Li, G., Peng, J., Li, K., & Wang, Z. (2022). Classroom learning status assessment based on deep learning. Mathematical Problems in Engineering, 2022, 7049458.
4. Peng, J., Yuan, B., Sun, M., Jiang, M., & Wang, M. (2022). Computer-based scaffolding for sustainable project-based learning: Impact on high- and low-achieving students. Sustainability, 14(19), 12907.
5. Li, Y., & Peng, J. (2022). Evaluation of expressive arts therapy on the resilience of university students in COVID-19: A network analysis approach. International Journal of Environmental Research and Public Health, 19(13), 7658.

Assist Prof Dr Jaya Singh Dhas L | Data Science | Best Researcher Award | 1229

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Assist Prof Dr Jaya Singh Dhas L | Data Science | Best Researcher Award

Head of the Department at Scott Christian College (Autonomous),India

Dr. L. Jaya Singh Dhas is the Head of the Department of Computer Science at Scott Christian College (Autonomous), Nagercoil, Tamil Nadu, India. With over two decades of experience in academia, Dr. Dhas is a distinguished researcher and educator, specializing in areas like Artificial Intelligence, Machine Learning, Data Mining, and Cloud Computing. His work combines theoretical research with practical applications, particularly in the fields of clustering techniques, heart disease prediction, and network security. Dr. Dhas has contributed significantly to the academic community through his research publications, conference participation, and various professional development activities.

Profile

Scopus

Education 🎓

  • Ph.D. in Computer Science – Bharathidasan University, Tiruchirappalli (2022), First Class
  • M.Phil. in Computer Science – Alagappa University, Karaikudi (1998), First Class
  • M.C.A. (Master of Computer Applications) – Bharathidasan University, Tiruchirappalli (1996), First Class
  • B.Sc. in Computer Science – Madurai Kamaraj University, Madurai (1991), First Class

Dr. Dhas’ academic qualifications reflect his deep commitment to the field of computer science and his expertise in both foundational and advanced topics within the discipline.

Professional Experience 💼

Dr. Dhas joined Scott Christian College (Autonomous) in 1998, where he has served as the Head of the Department of Computer Science since then. With more than 20 years of teaching and leadership experience, Dr. Dhas has significantly influenced the department’s curriculum and research direction. He is dedicated to fostering academic growth and promoting innovative research among students and faculty.

Research Interests 🔬

Dr. Dhas’ primary research interests lie in Artificial Intelligence, Data Science, Clustering Techniques, Big Data Analytics, and Network Security. He has worked extensively on the following areas:

  • Clustering Techniques: Investigating different clustering algorithms for analyzing temporal relational data.
  • Heart Disease Prediction: Using machine learning techniques for early-stage heart disease prediction.
  • Network Intrusion Detection: Optimizing deep learning approaches for network security.
  • Big Data: Exploring synergetic filtering and neural network techniques for handling large datasets.

Awards & Honors 🏆

Dr. Dhas has received multiple recognitions for his outstanding contributions in research and education, including:

  • Indian Patent (2022) for “Monitoring E-Health Care System Using Artificial Intelligence Techniques”.
  • Member of the Internet Society and International Association of Engineers (IAENG), further reflecting his international recognition in the field.
  • Reviewer for several renowned journals, including International Journal of Information Technology and Decision Making (IJITDM) and Journal of Scientific Research and Reports (JSRR).

Achievements 🌟

  • Successfully published numerous papers in high-impact journals such as Expert Systems With Applications (Elsevier), International Journal of Engineering and Advanced Technology (IJEAT), and Indian Journal of Natural Sciences (IJONS).
  • Served as a reviewer for several prestigious international journals and conferences, contributing to the academic community’s growth.
  • Authored multiple book chapters in edited volumes on topics like data clustering and artificial intelligence, further establishing his expertise.

Upcoming Projects 🚀

  • Dr. Dhas is currently engaged in projects related to AI-driven healthcare systems, particularly focusing on AI in early disease detection.
  • He is also exploring the use of neural networks and big data analytics to tackle contemporary challenges in network security and data privacy.

Publications 📚

  1. “Hybrid Fast Correlation-based Feature Selection with Improved Weighed Particle Swarm Optimization to Predict and Classify Heart Disease at an Early Stage”, Indian Journal of Natural Sciences (IJONS), Vol. 15, Issue 85, August 2024, Pages 76542 – 76550.
  2. “Network Intrusion Detection: An Optimized Deep Learning Approach Using Big Data Analytics”, Expert Systems With Applications, Elsevier, Volume 251, 1 October 2024, 123919.
  3. “Kulczynski Similarity Index Feature Selection based Map Estimated Rocchio Classification for Brain Tumor Disease Diagnosis”, International Journal on Recent and Innovation Trends in Computing and Communication (IJRITCC), December 2023.
  4. “Identification of Clustering Techniques with Temporal Relational Data Points”, International Journal of Interdisciplinary Global Studies (IJIGS), Volume 14, Issue 04, Oct-Dec’ 2020.
  5. “Efficient Synergetic Filtering in Big Dataset using Neural Network Technique”, International Journal of Recent Technology and Engineering (IJRTE), Volume 8, Issue 5, January 2020, Pages 1349 – 1360.