Junwei Du | Computer Science | Best Researcher Award

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Prof. Junwei Du | Computer Science | Best Researcher Award

Qingdao University of Science and Technology | China

Author Profile

Scopus

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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

 

Manyu Xiao | Mathematics | Best Researcher Award

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Assoc Prof Dr. Manyu Xiao | Mathematics | Best Researcher Award

Northwestern Polytechnical University | China

Author Profile

Scopus

Early Academic Pursuits

Dr. Manyu Xiao began her academic journey at Three Gorges University in China, where she earned her Bachelor of Science in Mathematics and Applied Mathematics in 2003. She then pursued a Master of Science in Computational Mathematics at Northwestern Polytechnical University (NPU), China, from 2003 to 2006. Her master’s research focused on fast and parallel algorithms for information processing under the guidance of Quanyi Lu. Subsequently, Dr. Xiao completed her Doctorate in Engineering Science from Université de Technologie de Compiègne (UTC) in France in 2010, where she specialized in multidisciplinary optimization with model reduction and parallel computing. Her doctoral advisors were Piotr Breitkopf and Rajan Filomeno Colho.

Professional Endeavors

Dr. Xiao has a rich professional background, marked by significant positions and research projects. Since March 2012, she has been an associate professor in the Department of Applied Mathematics at NPU. Prior to this, she was a post-doctoral fellow at UTC, France, from 2010 to 2011, where she worked on constrained POD model reductions. Her career includes various visiting scholar positions, such as at Université Libre de Bruxelles, Belgium, the University of Alabama in Huntsville, USA, Queen Mary University of London, University of Oxford, University of Cambridge, and University of Helsinki, Finland.

Contributions and Research Focus

Dr. Xiao’s research interests are diverse and impactful, focusing on efficient numerical methods, model reduction, parallel computing, mechanical optimization, and surrogate-based topology optimization. She has led and participated in numerous research projects, including those funded by the National Natural Science Foundation of China and the Natural Science Foundation of Shaanxi Province. Her projects cover areas such as dynamic multi-fidelity reduction for topology optimization, large-scale stress-constrained topology optimization, and the design of lightweight functional graded core structures for thermal protection systems.

Accolades and Recognition

Dr. Xiao’s contributions have been widely recognized. She received the Best Paper Award at the 6th Australian Conference on Computational Mechanics in 2023, and the third prize for outstanding academic paper by the Shaanxi province in 2022. In 2020, she was honored as an International Rising Star by the International Association for Computational Mechanics. Additionally, she has been recognized multiple times by Northwestern Polytechnical University for her teaching excellence and her role as a thesis supervisor.

Impact and Influence

Dr. Xiao’s work has significantly influenced the field of applied mathematics and computational mechanics. Her research on large-scale structural topology optimization and model reduction has advanced the capabilities of computational methods in engineering. Her numerous publications in high-impact journals and contributions to books underscore her influence. Furthermore, her teaching reforms and MOOC projects at NPU have enhanced the internationalization and quality of mathematics education.

Legacy and Future Contributions

Dr. Xiao’s legacy lies in her pioneering research and dedication to education. Her work continues to inspire advancements in computational mathematics and engineering optimization. Future contributions are anticipated from her ongoing and upcoming research projects, including those on the construction of kinetic models for composite materials and large-scale structural design optimization. Her commitment to developing internationalized training modes for mathematical talents ensures that her influence will extend to future generations of scholars and engineers.

 

Notable Publications

📄 Article: Primal–dual on-the-fly reduced-order modeling for large-scale transient dynamic topology optimization

  • Authors: Xiao, M., Ma, J., Gao, X., Cauvin, L., Villon, P.
  • Journal: Computer Methods in Applied Mechanics and Engineering
  • Year: 2024
  • Citations: 0

📄 Article: Towards a data-driven paradigm for characterizing plastic anisotropy using principal components analysis and manifold learning

  • Authors: Jin, J., Cauvin, L., Raghavan, B., Dutta, S., Xiao, M.
  • Journal: Computational Materials Science
  • Year: 2024
  • Citations: 0

📄 Article: Stress-constrained topology optimization using approximate reanalysis with on-the-fly reduced order modeling

  • Authors: Xiao, M., Ma, J., Lu, D., Raghavan, B., Zhang, W.
  • Journal: Advanced Modeling and Simulation in Engineering Sciences
  • Year: 2022
  • Citations: 1

📄 Article: A Gaussian process regression-based surrogate model of the varying workpiece dynamics for chatter prediction in milling of thin-walled structures

  • Authors: Yang, Y., Yang, Y., Xiao, M., Wan, M., Zhang, W.
  • Journal: International Journal of Mechanical System Dynamics
  • Year: 2022
  • Citations: 7

📄 Article: Accelerating Large-scale Topology Optimization: State-of-the-Art and Challenges

  • Authors: Mukherjee, S., Lu, D., Raghavan, B., Xiao, M., Zhang, W.
  • Journal: Archives of Computational Methods in Engineering
  • Year: 2021
  • Citations: 54