Mr. Ro-Yu Wu | Computer Science | Research Excellence Award

Mr. Ro-Yu Wu | Computer Science | Research Excellence Award

Professor | Lunghwa University of Science and Technology | Taiwan

Mr. Ro-Yu Wu is a Taiwan-based researcher recognized for his contributions to combinatorial algorithms, graph theory, and efficient data structures, particularly within the domains of ranking and unranking methods, Hamiltonian graph properties, and algorithmic generation of combinatorial objects. As a productive scholar in theoretical computer science and industrial management, his work emphasizes the design of loopless, lexicographic, and Gray code–based algorithms that enhance computational efficiency and fault-tolerant communication in complex networks. His research is well acknowledged in the global academic community, as reflected in his Scopus record with 45 documents, 308 citations across 189 citing works, and an h-index of 10. On ResearchGate, he maintains an active profile with 47 publications, over 6,300 reads, and 367 citations. These metrics highlight his growing influence, especially in areas involving structured graph traversal, spanning-tree generation, and the analytical foundations supporting optimization and data broadcasting systems. His work frequently explores practical algorithmic strategies for high-performance computing environments, providing innovative insights for fault-tolerant network design and combinatorial enumeration. Mr. Wu’s collaborations span multi-author research teams, contributing to advancements published in high-impact venues such as Theoretical Computer Science, The Journal of Supercomputing, Journal of Combinatorial Optimization, and Optimization Letters. His ongoing research continues to shape efficient computational paradigms for combinatorial structures, making him a relevant contributor to the future of theoretical and applied algorithmic studies.

Profile

Scopus

Featured Publications 

Xie, Z., Wu, R.-Y., & Shi, L. (2025). Ranking and unranking algorithms for derangements based on lexicographical order. Theoretical Computer Science.

Pai, K.-J., Wu, R.-Y., Peng, S. L., & Chang, J. M. (2023). Three edge-disjoint Hamiltonian cycles in crossed cubes with applications to fault-tolerant data broadcasting. The Journal of Supercomputing.

Chang, Y. H., Wu, R.-Y., Chang, R. S., & Chang, J. M. (2022). Improved algorithms for ranking and unranking (k, m)-ary trees in B-order. Journal of Combinatorial Optimization.

Wu, R.-Y., Tseng, C. C., Hung, L. J., & Chang, J. M. (2022). Generating spanning-tree sequences of a fan graph in lexicographic order and ranking/unranking algorithms. International Symposium on Combinatorial Optimization.

Chang, Y. H., Wu, R.-Y., Lin, C. K., & Chang, J. M. (2021). A loopless algorithm for generating (k, m)-ary trees in Gray code order. Optimization Letters.

Hsin-Yuan Chen | Computer Science | Best Researcher Award

Prof. Hsin-Yuan Chen | Computer Science | Best Researcher Award

Zhejiang University | China

Prof. Hsin-Yuan Chen is a distinguished scholar and technology leader known for his extensive contributions to artificial intelligence, robotics, and digital technology innovation. He currently serves as the Changjiang Scholar Professor and Director at Zhejiang University’s Institute of Wenzhou, Center of Digital Technology Entrepreneurship and Innovation in China, as well as Adjunct Distinguished Professor at Patil University in India. With an academic and professional journey spanning universities, research institutes, and top technology companies, Prof. Chen has built a reputation for pioneering research, impactful industry collaborations, and leadership in advancing global technology ecosystems.

Publication Profile

Scopus

ORCID

Education Background

Prof. Hsin-Yuan Chen pursued his academic studies at National Cheng Kung University, where he earned both his Bachelor’s and Ph.D. degrees in Aerospace Engineering, completing his doctoral program directly after undergraduate study. His rigorous academic foundation combined with a strong focus on applied research shaped his career path, enabling him to bridge advanced engineering knowledge with emerging fields like artificial intelligence and big data. His educational achievements not only established him as a capable researcher but also laid the groundwork for his future endeavors in academia, technology innovation, and international collaborations across multiple institutions and disciplines.

Professional Experience

Prof. Hsin-Yuan Chen has held numerous leadership and academic roles across diverse sectors. He served as Dean and Professor at Fujian Normal University’s School of Big Data and Artificial Intelligence, and also held CTO positions at GEOSAT Technology and Mobiletron Electronics, leading artificial intelligence applications in industry. His early career included academic appointments at Feng Chia University and National Taiwan Ocean University, alongside international experience as Visiting Professor at Washington University in St. Louis. Additionally, he contributed to public service as a Patent Examiner at the Intellectual Property Office and worked with Delta Electronics as Technical Advisor, balancing academia with industrial innovation.

Awards and Honors

Prof. Hsin-Yuan Chen has been widely recognized with prestigious national and international awards. His accolades include the ScienceFather International Outstanding Scientist Award, the Electronics Best Paper Award, and fellowship honors from IET and ASEAN. He has also received multiple innovation and creativity awards for projects in virtual reality, artificial intelligence, and cloud technology, particularly in digital cultural heritage applications. Earlier distinctions include the Global Top Hundred Engineers Medal, Youth Medal of the Republic of China, and recognition as one of the Top Ten Outstanding Young Women in the Republic of China. His achievements highlight his dedication to research, teaching, and technological innovation.

Research Focus

Prof. Hsin-Yuan Chen’s research primarily spans artificial intelligence, robotics, big data, digital innovation, and human-centered computing. He has extensively explored AI applications in fields such as healthcare, education, and cultural heritage digitalization. His work includes developing hybrid positioning systems, AI-driven recognition technologies, and bibliometric studies in AI applications. He has also focused on advancing industry-academia collaboration and integrating emerging technologies like VR, AR, and IoT into practical solutions. Through his contributions, Prof. Chen has advanced both theoretical research and applied science, strengthening connections between innovation, entrepreneurship, and real-world societal impact in the digital era.

Publication Notes

  1. Evaluating Machine Learning Algorithms for Alzheimer’s Detection: A Comprehensive Analysis
    Published Year: 2025
    Citation: 1

  2. Impact of Industry-Academia Collaboration in Engineering Education: A Case Study
    Published Year: 2025
    Citation: 3

  3. Recursive Queried Frequent Patterns Algorithm: Determining Frequent Pattern Sets from Database
    Published Year: 2025
    Citation: 2

  4. Mapping the Evolution: A Bibliometric Analysis of Employee Engagement and Performance in the Age of AI-Based Solutions
    Published Year: 2025
    Citation: 1

  5. Advancements in Handwritten Devanagari Character Recognition: A Study on Transfer Learning and VGG16 Algorithm
    Published Year: 2024
    Citation: 1

Conclusion

Prof. Hsin-Yuan Chen’s career exemplifies the synergy between academic excellence and industrial innovation. With a solid foundation in aerospace engineering, he has consistently expanded his expertise into artificial intelligence, robotics, and digital transformation. His leadership roles across universities, research institutions, and technology enterprises demonstrate his global influence, while his awards reflect recognition for outstanding achievements in both research and practice. As an educator, innovator, and scientist, Prof. Chen continues to inspire through his contributions to emerging technologies and his efforts in building bridges between academia and industry to shape the future of digital transformation.