Taylor's University | Malaysia

Assoc. Prof. Dr. Saraswathy Shamini Gunasekaran is an accomplished researcher and academic specializing in Artificial Intelligence, with a strong focus on agent-based systems, intelligent autonomous systems, machine learning applications, smart energy systems, and climate change–related digital intelligence. Her scholarly impact is reflected in an h-index of 16, with 70 research documents generating 899 citations across international indexing platforms, demonstrating sustained influence in AI-driven and interdisciplinary research domains. Her work spans collective intelligence, knowledge transfer models, data mining, educational technologies, and intelligent digitalization, with publications appearing in IEEE conferences, international journals, and Springer book chapters. In addition to academic publishing, she has led significant intellectual property initiatives, including a granted patent on cooperative control systems for unmanned aerial platforms, utility innovations in autonomous multi-UAV task allocation, and copyrighted micro-credential programs. Her research excellence has been recognized through multiple prestigious awards, including international science communication accolades, industry research honors, and selection for global digital leadership programs. With over two decades of academic engagement and active research contributions, her profile reflects a strong integration of theoretical innovation, applied intelligence systems, and impactful scholarly dissemination across AI, energy, education, and digital transformation domains.

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View Scopus Profile

Featured Publications

Catalytic performance of Cr:Ca/γ-Al₂O₃ for triolein transesterification: mechanistic pathways via Langmuir–Hinshelwood–Hougen–Watson model, kinetic analysis, and RSM optimization
– Inorganic Chemistry Communications, 2025

A Deep Learning-based Fault Detection and Classification in Smart Electrical Power Transmission System
– JOIV: International Journal on Informatics Visualization, 2024

An agent architecture for autonomous UAV flight control in object classification and recognition missions
– Soft Computing, 2023

An Automated Image Segmentation and Useful Feature Extraction Algorithm for Retinal Blood Vessels in Fundus Images
– Electronics, 2022

Exploring the Roles of Agents and Multi-Agent in Improving Mobile Ad Hoc Networks
– International Symposium on Agents, Multi-Agent Systems and Robotics, ISAMSR, 2021

Haiwei Wu | Engineering | Best Researcher Award

Published on 09/12/202509/12/2025 by Book of Award

Prof. Dr. Haiwei Wu | Engineering | Best Researcher Award

Jilin Agricultural University | China

Prof. Dr. Haiwei Wu is an emerging multidisciplinary researcher whose contributions span energy systems, machine learning, spectroscopy, and intelligent diagnostics. His recent research focuses on advanced computational methods applied to energy storage and electric vehicle systems, including the development of an attention-based multi-feature fusion physics-informed neural network for accurate state-of-health estimation of lithium-ion batteries and the application of queuing-theoretic models for sustainable EV charging infrastructure planning. Beyond energy research, he has contributed significantly to the use of mid-infrared spectroscopy combined with machine learning and support vector machines for the authentication and identification of biological and agricultural products, reflecting strong capabilities in analytical modeling and pattern recognition. His publications from 2022 to 2025 highlight expertise in spectral analysis, counterfeit detection, and quality assessment. In addition, he has explored applications of improved YOLOv8 for mechanical part inspection and contributed to research on task-driven cooperative inquiry learning in education. His innovative work is supported by several patents related to electric vehicle charging technologies, demonstrating a commitment to advancing practical, technology-driven solutions across sectors.

Profile : Scopus | Orcid

Featured Publications

Wu, H., Liu, J., Wang, Z., & Li, X. (2025). An attention-based multi-feature fusion physics-informed neural network for state-of-health estimation of lithium-ion batteries. Energies.

Wang, Z., Zou, J., Tu, J., Li, X., Liu, J., & Wu, H. (2025). Towards sustainable EV infrastructure: Site selection and capacity planning with charger type differentiation and queuing-theoretic modeling. World Electric Vehicle Journal.

He, T., Kaimin, W., & Wu, H. (2025). Research on the construction and implementation of a task-driven cooperative inquiry learning model for postgraduate students majoring in music education. Chinese Music Education, (05), 47–53.

Yang, C.-E., Wu, H., Yuan, Y., et al. (2025). Efficient recognition of plum blossom antler hats and red deer antler hats based on support vector machine and mid-infrared spectroscopy. Journal of Jilin Agricultural University, 1–7.

Yang, C.-E., Su, L., Feng, W.-Z., Zhou, J.-Y., Wu, H.-W., Yuan, Y.-M., & Wang, Q. (2023). Identification of Pleurotus ostreatus from different producing areas based on mid-infrared spectroscopy and machine learning. Spectroscopy and Spectral Analysis.

Yang, C.-E., Su, L., Feng, W., et al. (2023). Identification of Pleurotus ostreatus from different origins by mid-infrared spectroscopy combined with machine learning. Spectroscopy and Spectral Analysis, 43(02), 577–582.

Yang, C.-E., Wu, H.-W., Yang, Y., Su, L., Yuan, Y.-M., Liu, H., Zhang, A.-W., & Song, Z.-Y. (2022). A model for the identification of counterfeited and adulterated Sika deer antler cap powder based on mid-infrared spectroscopy and support vector machines. Spectroscopy and Spectral Analysis.

Yang, C.-E., Wu, H., Yang, Y., et al. (2022). Identification model of counterfeiting and adulteration of plum blossom antler cap powder based on mid-infrared spectroscopy and support vector machine. Spectroscopy and Spectral Analysis, 42(08), 2359–2365.

Victor R.L. Shen | Computer Science | Best Researcher Award

Published on 27/09/202527/09/2025 by Book of Award

Prof. Dr. Victor R.L. Shen | Computer Science | Best Researcher Award

National Taipei University | Taiwan

Prof. Dr. Victor R. L. Shen is a highly accomplished scholar and Professor Emeritus in the Department of Computer Science and Information Engineering at National Taipei University, Taiwan. With an extensive academic background, including a Ph.D. in Computer Science from National Taiwan University, he has dedicated decades to advancing research and education in artificial intelligence, Petri net theory, fuzzy logic, cryptography, e-learning systems, IoT, and intelligent computing. Over his distinguished career, he has published 78 documents that collectively received 840 citations across 696 sources, earning him an h-index of 15, reflecting both the depth and impact of his contributions. Beyond his prolific research, Prof. Shen has held prominent academic leadership positions, including Dean, Chairman, and CEO roles at National Taipei University and Ming Chi University of Technology, shaping academic programs and fostering innovation. His global recognition includes visiting professorships, membership in leading professional organizations such as IEEE, ACM, and IET, and numerous prestigious awards for teaching, research, and innovation. With sustained contributions in smart systems, advanced computing, and AI-driven education, Prof. Shen continues to influence the global academic community, leaving a legacy of excellence in both research and pedagogy.

Profiles : Scopus | Orcid

Featured Publications

Yang, C.-Y., Lin, Y.-N., Shen, V. R. L., Shen, F. H. C., & Lin, Y.-C. (2025). Petri net modeling and analysis of an IoT-enabled system for real-time monitoring of eggplants. Systems Engineering.

Yang, C.-Y., Lin, Y.-N., Shen, V. R. L., Shen, F. H. C., & Jheng, W.-S. (2025). A novel IoT-enabled system for real-time monitoring home appliances using Petri nets. IEEE Canadian Journal of Electrical and Computer Engineering.

Chang, J.-C., Chen, S.-A., & Shen, V. R. L. (2024). Smart bird identification system based on a hybrid approach: Petri nets, convolutional neural and deep residual networks. Multimedia Tools and Applications, 83(12), 34795–34823.

Yang, C.-Y., Lin, Y.-N., Shen, V. R. L., Tung, Y.-C., & Lin, J.-F. (2024). A novel IoT-enabled system for real-time face mask recognition based on Petri nets. IEEE Internet of Things Journal, 11(4), 6992–7001.

Yang, C.-Y., Lin, Y.-N., Wang, S.-K., Shen, V. R. L., & Lin, Y.-C. (2024). An edge computing system for fast image recognition based on convolutional neural network and Petri net model. Multimedia Tools and Applications, 83(5), 12849–12873.

Yang, C.-Y., Hwang, M.-S., Tseng, Y.-W., Yang, C.-C., & Shen, V. R. L. (2024). Advancing financial forecasts: Stock price prediction based on time series and machine learning techniques. Applied Artificial Intelligence, 38(1), 1–24.

Lin, Y.-N., Wang, S.-K., Chiou, G.-J., Yang, C.-Y., Shen, V. R. L., & Su, Z. Y. (2023). Development and verification of an IoT-enabled air quality monitoring system based on Petri nets. Wireless Personal Communications, 131(1), 63–87.*

Junwei Du | Computer Science | Best Researcher Award

Published on 17/12/202417/12/2024 by Book of Award

Prof. Junwei Du | Computer Science | Best Researcher Award

Qingdao University of Science and Technology | China

Author Profile

Scopus

Orcid

Early Academic Pursuits 🎓

Prof. Junwei Du embarked on his academic journey with a strong foundation in computer science. He earned his Ph.D. in Computer Software and Theory from Tongji University in 2010. His thirst for international exposure led him to become a Visiting Scholar at Arizona State University, USA, in 2014. Further enriching his skills, Prof. Du attended the AI Training Workshop for Young Backbone hosted by the University of Queensland and the University of Technology, Sydney, Australia, in September 2018.

Professional Endeavors 💼

Prof. Junwei Du is currently Executive Vice Dean of the School of Data Science at Qingdao University of Science and Technology. His professional affiliations include being a Distinguished Member of CCF and holding memberships in prestigious committees like the China Computer Society's Software Engineering Specialised Committee and the China Automation Society's Network Information Service Committee. Additionally, he serves as a Director of the Shandong Artificial Intelligence Society, underscoring his leadership in the field.

Contributions and Research Focus 🔬

Prof. Du's research focuses on cutting-edge areas like intelligent software engineering, graph representation learning, and recommendation algorithms. He has led numerous high-impact projects, including a National Natural Science Foundation of China top-level project, two provincial funds, and a key R&D project in Shandong Province. His work has also extended to over 10 national vertical projects and nine enterprise-driven horizontal projects. Prof. Du has published more than 60 academic papers in renowned journals such as Information Sciences, Software Journal, and Expert Systems with Applications. His research has significantly contributed to software fault prediction, cross-domain recommendation systems, and privacy-preserving algorithms in IoT.

Accolades and Recognition 🏆

Prof. Junwei Du’s achievements have earned him notable accolades. As a key participant, he received the Third Prize of Shandong Provincial Scientific and Technological Progress and the Third Prize of Shandong Provincial Teaching Achievement. He has also guided his students to excel in prestigious competitions, leading them to win over 20 national awards in software design and testing.

Impact and Influence 🌍

Through his extensive contributions, Prof. Junwei Du has shaped the landscape of intelligent software systems and data science education. His leadership in research and teaching has inspired countless students to pursue innovation. Prof. Du’s work on ensemble learning, recommendation algorithms, and software fault prediction holds significant implications for industries ranging from IT to industrial IoT, enhancing technological efficiency and reliability.

Legacy and Future Contributions 🔮

Prof. Junwei Du continues to build a legacy of excellence, bridging academia and industry with transformative research and mentorship. His focus on emerging areas like graph representation learning and cross-domain recommendation systems will pave the way for smarter AI applications. By fostering collaboration and innovation, he is set to make lasting contributions to data science and software engineering, empowering the next generation of researchers and professionals.

Publications

📄 Improving Bug Triage with the Bug Personalized Tossing Relationship
Authors: Wei Wei, Haojie Li, Xinshuang Ren, Feng Jiang, Xu Yu, Xingyu Gao, Junwei Du
Journal: Information and Software Technology
Year: 2025

📄 A Privacy-Preserving Cross-Domain Recommendation Algorithm for Industrial IoT Devices
Authors: Yu X., Peng Q., Lv H., Du J., Gong D.
Journal: IEEE Transactions on Consumer Electronics
Year: 2024

📄 Research on Efficient Data Warehouse Construction Methods for Big Data Applications
Authors: Zhao C., Du J., Wang F., Li H.
Journal: Applied Mathematics and Nonlinear Sciences
Year: 2024

📄 A Cross-Domain Intrusion Detection Method Based on Nonlinear Augmented Explicit Features
Authors: Yu X., Lu Y., Jiang F., Du J., Gong D.
Journal: IEEE Transactions on Network and Service Management
Year: 2024

📄 A Multi-Behavior Recommendation Based on Disentangled Graph Convolutional Networks and Contrastive Learning
Authors: Yu J., Jiang F., Du J.W., Yu X.
Journal/Proceedings: Communications in Computer and Information Science
Year: 2024

Yang Liu | Computer Science | Best Researcher Award

Published on 21/06/202421/06/2024 by Book of Award

Prof. Yang Liu | Computer Science | Best Researcher Award

Henan University of Technology | China

Author Profile

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Early Academic Pursuits

Prof. Yang Liu was born in November 1978. She pursued her academic journey in the field of Computer Science, culminating in a Ph.D. from the School of Computer Science at Northwestern Polytechnical University (NWTU) between September 2003 and November 2007. Her early academic career set a strong foundation for her expertise in distributed computing and blockchain technology.

Professional Endeavors

After earning her Ph.D., Prof. Liu began her professional career as an Assistant Researcher at the Shenzhen Institutes of Advanced Technology, part of the China Academy of Sciences, from November 2007 to February 2009. Since March 2009, she has been a Professor at the College of Information Science and Engineering, Henan University of Technology (HAUT). Her professional journey has been marked by significant contributions to academia and research, particularly in the realms of distributed computing and blockchain.

Contributions and Research Focus

Prof. Liu's research interests are deeply rooted in distributed computing and blockchain technology, focusing on developing secure and efficient consensus mechanisms in blockchain systems, implementing blockchain-based solutions for food traceability and circulation, and researching adaptive resource scheduling and allocation mechanisms in cloud environments. Her contributions extend to developing distributed computing technologies tailored for big data domains. Prof. Liu's work has been instrumental in advancing the practical application and theoretical understanding of these technologies, significantly impacting various real-world scenarios.

Accolades and Recognition

Prof. Liu has garnered numerous awards and honors, underscoring her substantial contributions to science and technology. These include being appointed Chief Science Expert of Henan Province in 2023, receiving the New Century Excellent Talents award from the Ministry of Education of China in 2012, and leading an Innovative Research Team in Science and Technology at the University of Henan Province in 2017. Her achievements also encompass the Prize of Scientific and Technological Achievements of Henan Province in 2013, along with the Henan Province Award for Outstanding Publications in Natural Science in 2011. These accolades affirm Prof. Liu's impactful role in advancing research and innovation, particularly within Henan Province and across China.

Impact and Influence

Prof. Liu's influence extends beyond her research into pivotal roles within various organizations. She serves as a Technical Committee Member for Systems Software and Blockchain at the China Computer Federation (CCF), highlighting her expertise in these critical fields. Additionally, as Deputy Director of the Academic Committee at the Henan Blockchain Technology Research Association and a member of the Experts Committee at the Zhengzhou Information Promote Association, she plays a significant role in shaping the future of computing and blockchain technology. Her leadership and contributions in these positions underscore her commitment to advancing these domains, both locally and on a broader scale.

Legacy and Future Contributions

Prof. Liu has authored numerous publications that have contributed to the body of knowledge in her field. Some notable works include research on consensus algorithms, cloud computing resource management, and energy-efficient communication in wireless sensor networks. Her ongoing research and future contributions are expected to further advance the fields of distributed computing and blockchain, influencing both academic research and practical applications.

Notable Publications

Towards secure and efficient integration of blockchain and 6G networks 2024

A Pipeline-based Chain Structure Byzantine Consensus Algorithm for Blockchain Systems 2023

SoK: Research status and challenges of blockchain smart contracts 2023

MoryFabric: Reducing Transaction Abort by Actual Validity Verification and Reordering 2023

Jingjing Cao | Computer Science | Best Researcher Award

Published on 16/03/202416/03/2024 by Book of Award

Dr. Jingjing Cao | Computer Science | Best Researcher Award

School of Transportation and Logistics Engineering | China

Author Profile

Scopus

Orcid

Early Academic Pursuits

Dr. Jingjing Cao's academic journey commenced with a Bachelor of Engineering in Information and Computing Science from Dalian Maritime University. Subsequently, she pursued a Master of Science in Applied Mathematics before earning her Ph.D. from the Department of Computer Science at City University of Hong Kong.

Professional Endeavors

Dr. Cao's professional journey has been marked by significant contributions. She served as a Research Associate at Dalian Maritime University and later assumed roles as Assistant Professor and now Tenure Track Associate Professor at Wuhan University of Technology.

Contributions and Research Focus

With a focus on Machine Learning and its applications in transportation and logistics, Dr. Cao has made remarkable contributions. Her research spans various domains, including ensemble learning, deep learning, and optimization algorithms, as evidenced by her prolific publication record in reputable journals and conferences.

Accolades and Recognition

Dr. Cao's impactful research has garnered widespread recognition, exemplified by her receipt of the prestigious Best Researcher Award. Her publications in renowned journals and conferences underscore her standing as a leading figure in the field of Computer Science and Machine Learning.

Impact and Influence

Dr. Cao's work has left a lasting impact on the academic community and industry alike. Her research has not only advanced the theoretical understanding of Machine Learning but has also found practical applications in domains such as transportation, logistics, and industrial informatics.

Legacy and Future Contributions

As Dr. Cao continues her academic journey, her legacy is defined by a commitment to excellence in research and education. With ongoing projects and professional services, she remains dedicated to shaping the future of Computer Science and Machine Learning, leaving an indelible mark on the field.

Notable Publication

A two-stage model for forecasting consumers’ intention to purchase with e-coupons 2021 (15)

RtDS: real-time distributed strategy for multi-period task offloading in vehicular edge computing environment 2021 (14)