Dongju Yang | Computer Science and Artificial Intelligence | Research Excellence Award

Dr. Dongju Yang | Computer Science and Artificial Intelligence | Research Excellence Award

North China University of Technology | China

Dr. Dongju Yang is an Associate Researcher and Assistant Lead Professor for Artificial Intelligence at North China University of Technology, with over a decade of academic and research experience in intelligent computing systems. She earned her Ph.D. in Computer Software and Theory from Northwestern Polytechnical University and previously conducted advanced research at the Institute of Computing Technology, Chinese Academy of Sciences. Her research focuses on Large Language Models, Retrieval-Augmented Generation (RAG), AI Agents, Knowledge Graphs, Natural Language Processing, Service Computing, and Data Intelligence, with strong application impact in smart elderly care and intelligent education. Dr. Yang has led more than ten competitive research projects as principal investigator, including a sub-project of China’s National Key R&D Program and an NSFC General Program, while contributing to multiple major national initiatives. She has contributed to one national standard and three group standards and received the Beijing Science and Technology Progress Award. Overall, her work bridges fundamental AI research with scalable, real-world technological impact and talent cultivation.


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Featured Publications

Intelligent Orientation Robot Based on Large Language Models and Retrieval-Augmented Generation
Dongju Yang, 5th International Conference on Artificial Intelligence and Computer Engineering (ICAICE), 2024. (WOS)

Multi-source Autoregressive Entity Linking Based on Generative Method
Dongju Yang, Weishui Lan, Communications in Computer and Information Science, 2024. (Book Chapter)

IoT Service Distributed Management Architecture and Service Discovery Method for Edge-Cloud Federation
Dongju Yang, International Journal of Grid and Utility Computing, 2022. (WOS)

Construction and Analysis of Scientific and Technological Personnel Relational Graph for Group Recognition
Dongju Yang, International Journal of Software Engineering and Knowledge Engineering, 2021. (WOS)

Research on User Demand-Driven Service Matching Methodology
Huiying Zhang, Dongju Yang, IEEE 6th International Conference on Cloud Computing and Big Data Analytics (ICCCBDA), 2021.

Adetayo Folorunso | Energy and Sustainability | Best Researcher Award

Dr. Adetayo Folorunso | Energy and Sustainability | Best Researcher Award

Federal University of Technology, Akure | Nigeria

Adetayo Folorunso is an established scholar in applied geophysics and environmental geosciences with a strong record of scientific contributions to groundwater, marine, and exploration geophysics.  Academic training and professional experience span geophysics, earth sciences, and applied geoscience, with extensive involvement in teaching, postgraduate supervision, and collaborative research across Nigerian and international institutions. Research work integrates electrical resistivity tomography (ERT), marine geophysics, hydrogeophysics, seismic interpretation, and environmental geophysics, addressing critical challenges such as saline water intrusion, groundwater vulnerability, subsurface contamination, and reservoir characterization. Contributions include high-impact journal articles, interdisciplinary studies combining geophysical and geochemical methods, and methodological advances in finite-element and CSEM modeling. Recognition includes scholarly visibility, sustained citation performance, and leadership in collaborative geoscience research. Overall, the body of work demonstrates a strong commitment to advancing applied geosciences through data-driven analysis, field-based investigations, and solutions relevant to environmental sustainability, resource exploration, and geotechnical risk assessment.

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Featured Publications


Integrated Geophysical and Geochemical Methods for Environmental Assessment of Municipal Dumpsite System

International Journal of Geosciences, 4(5), 850–862, 2013 · Citations: 59


Engineering Site Characterisation Using 2-D and 3-D Electrical Resistivity Tomography

Earth Science Research, 2(1), 133–142, 2013 · Citations: 41