Yuanhui Liang | Intelligent Communication | Best Researcher Award

Published on by Global CSE Awards

Best Researcher Award

Yuanhui Liang
Sichuan University of Science and Engineering
               Yuanhui Liang
Affiliation Sichuan University of Science and Engineering
Country China
Scopus ID 57227741600
Documents 19
Citations 72
h-index 5
Subject Area Intelligent Communication
Event Global CSE Awards
ORCID 0009-0003-1247-2451

Yuanhui Liang is a researcher affiliated with Sichuan University of Science and Engineering, China, whose academic contributions are associated with intelligent communication systems, neural decoding methodologies, and data-driven communication technologies. The scholarly profile demonstrates active engagement in modern wireless communication research, with publications indexed in Scopus and related citation impact indicators.[1]

Abstract

This article presents an academic overview of Yuanhui Liang and associated research activities within intelligent communication systems. The profile highlights contributions to neural decoding, communication optimization, and low-complexity data-driven communication methods. The available publication and citation records indicate scholarly engagement and continuing participation in advanced communication engineering research.[1]

Keywords

Intelligent Communication, Neural Decoding, Data-Driven Communication, Channel Coding, Wireless Communication, Tensor Ring Decomposition, Communication Systems, Artificial Intelligence, Neural Receivers, Information Engineering.

Introduction

Yuanhui Liang has participated in research associated with intelligent communication technologies and neural decoding systems. The research profile reflects involvement in data-driven communication optimization, wireless communication methodologies, and low-complexity neural receiver development. These activities contribute to ongoing advancements in efficient communication system performance and modern signal processing research.[1][2]

Research Profile

The available Scopus-indexed profile demonstrates academic activity in intelligent communication and computational communication engineering. Research outputs include collaborative publications involving neural decoding algorithms, communication neural receivers, and machine learning-assisted communication frameworks. Citation indicators and indexed documents collectively illustrate an emerging scholarly presence within contemporary communication research fields.[1]

Research Contributions

The researcher has contributed to low-complexity neural belief propagation decoding algorithms, hypernetwork-based channel neural decoding models, and communication neural receiver optimization techniques. These studies support efficient data transmission, decoding accuracy, and computational optimization in intelligent communication systems while integrating artificial intelligence approaches into modern wireless communication architectures.[1][2][3]

Publications

The publication record includes research articles published in IEEE journals focusing on intelligent communication systems, neural decoding methodologies, and low-complexity communication algorithms. The documented publications demonstrate collaborative academic participation and contribute to literature concerning communication optimization, tensor decomposition techniques, and machine learning-assisted communication frameworks.[1][2][3]

Research Impact

The research contributions demonstrate relevance to intelligent communication engineering and modern neural decoding research. Indexed publications and citation metrics indicate measurable scholarly visibility. The focus on computationally efficient communication solutions may support future developments in wireless communication reliability, artificial intelligence integration, and advanced communication network optimization methodologies.[1]

Award Suitability

Based on the available academic profile, Yuanhui Liang demonstrates consistent scholarly participation in intelligent communication research and neural decoding technologies. The combination of indexed publications, collaborative research output, and citation visibility supports consideration for academic recognition within communication engineering and computational communication research domains.[1][2]

Conclusion

Yuanhui Liang has established an emerging research profile in intelligent communication and neural decoding systems through collaborative publications and indexed scholarly contributions. The documented work reflects participation in contemporary communication engineering research and supports recognition for contributions related to efficient communication algorithms and intelligent communication methodologies.[1][3]

References

  1. Wu, Q., Liang, Y., Ng, B. K., Lam, C.-T., & Ma, Y. (2024). Low-Complexity Data-Driven Communication Neural Receivers. IEEE Access.
    DOI: https://doi.org/10.1109/access.2024.3524571
  2. Liang, Y., Lam, C.-T., Wu, Q., Ng, B. K., & Im, S.-K. (2024). Hypernetwork Based Model-Driven Channel Neural Decoding. IEEE Access.
    DOI: https://doi.org/10.1109/access.2024.3400367
  3. Liang, Y., Lam, C.-T., Wu, Q., Ng, B. K., & Im, S. K. (2024). Low-Complexity Neural Belief Propagation Decoding Algorithm Based on Tensor Ring Decomposition. IEEE Transactions on Cognitive Communications and Networking.
    DOI: https://doi.org/10.1109/tccn.2024.3487999
  4. Elsevier. (n.d.). Scopus author details: Yuanhui Liang, Author ID 57227741600. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57227741600
  5. ORCID. (n.d.). Yuanhui Liang ORCID profile.
    https://orcid.org/0009-0003-1247-2451

Mitsuru Endo | Computational Theory | Best Researcher Award

Published on by Global CSE Awards

Prof. Dr. Mitsuru Endo | Computational Theory | Best Researcher Award

Professor Emeritus| Tokyo Institute of Technology | Japan

Mitsuru Endo has made distinguished contributions to applied mechanics and vibration engineering, focusing on the dynamic behavior of continua and structures and the development of advanced noise and vibration control systems. His work bridges theoretical mechanics and practical applications in acoustic control, offering innovative solutions for vibration reduction in engineering systems. Endo has pioneered the extension of Southwell-Dunkerley methods for synthesizing frequencies, contributing to a deeper understanding of vibrational modes in complex systems. His research on flexural vibrations of rotating rings and deformation theories for beams, plates, and cylindrical shells has advanced modeling precision in mechanical structures. By introducing alternative formulations for Timoshenko beam and Mindlin plate models, Endo improved computational accuracy in vibration analysis. His innovative “one-half order shear deformation theory” redefined how transverse shear deformation is represented in structural mechanics, influencing global research on elasticity and composite structures. Endo’s extensive publications in leading journals such as the Journal of Sound and Vibration and the International Journal of Mechanical Sciences have established a strong foundation for future explorations in vibration modeling, acoustic optimization, and structural mechanics. His studies integrate both analytical and experimental perspectives, driving advancements in passive and active noise control technologies essential to aerospace, automotive, and civil engineering applications. The recognition of his work through multiple prestigious awards underscores his impact in mechanical sciences and engineering research, with 440 citations, 64 documents, and an h-index of 8.

Profiles: Scopus | ORCID
Featured Publication

Endo, M. (2013). Study on direct sound reduction structure for reducing noise generated by vibrating solids. Journal of Sound and Vibration, 332, 2643–2658. 5 citations

Endo, M. (2015). Study on an alternative deformation concept for the Timoshenko beam and Mindlin plate models. International Journal of Engineering Science, 87, 32–56. 34 citations

Endo, M. (2016). An alternative first-order shear deformation concept and its application to beam, plate and cylindrical shell models. Composite Structures, 146, 50–61. 17 citations

Endo, M. (n.d.). Study on the characteristics of noise reduction effects of a sound reduction structure. Conference Paper. 1 citation

Arif Basgumus | Mobile Computing | Best Researcher Award

Published on by Global CSE Awards

Dr. Arif Basgumus | Mobile Computing | Best Researcher Award

Associate Professor | Bursa Uludag University | Turkey

Dr. Arif Basgumus is a distinguished Associate Professor at Bursa Uludag University, whose research profoundly advances wireless communication, signal processing, and next-generation network systems. His extensive contributions encompass cognitive radio networks, non-orthogonal multiple access (NOMA), reconfigurable intelligent surfaces (RIS), cooperative communications, integrated sensing and communication (ISAC), and physical layer security. Dr. Arif Basgumus has developed robust models for interference alignment, hybrid RF/VLC systems, and UAV-assisted network architectures, contributing significantly to 5G and 6G technology evolution. His studies integrate theoretical modeling with artificial intelligence applications, enhancing the efficiency and reliability of communication frameworks. Actively collaborating with industrial partners such as ASELSAN, HAVELSAN, and TUSAŞ, he bridges academic innovation with practical defense and aerospace applications. His authorship spans influential journals including IEEE Access, IET Communications, and Digital Signal Processing, reflecting a consistent research impact in signal optimization, deep learning-aided communications, and security enhancement in RIS-assisted systems. He has guided numerous graduate theses, emphasizing interdisciplinary approaches across electrical, electronics, and computer engineering. His projects funded by TUBITAK and other research councils explore UAV communication, smart vehicle systems, and optical sensor networks, fostering sustainable and intelligent connectivity. Dr. Arif Basgumus has also co-authored several books and chapters on communication systems, cognitive networks, and artificial intelligence in engineering. His long-standing involvement in international collaborations and IEEE activities highlights a leadership role in shaping the technological foundations of future communication infrastructures, with 256 citations, 48 documents, and an h-index of 10 (View h-index).

Profiles:  Google Scholar | Scopus | ORCID
Featured Publication

Alakoca, H., Namdar, M., Aldirmaz-Colak, S., Basaran, M., & Basgumus, A. (2022). Metasurface manipulation attacks: Potential security threats of RIS-aided 6G communications. IEEE Communications Magazine, 61(1), 24–30. Citations: 43

Bayhan, E., Ozkan, Z., Namdar, M., & Basgumus, A. (2021). Deep learning-based object detection and recognition of unmanned aerial vehicles. In Proceedings of the 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications. Citations: 41

Ozkan, Z., Bayhan, E., Namdar, M., & Basgumus, A. (2021). Object detection and recognition of unmanned aerial vehicles using Raspberry Pi platform. In Proceedings of the 5th International Symposium on Multidisciplinary Studies and Innovative Technologies. Citations: 34

Altuncu, A., & Basgumus, A. (2005). Gain enhancement in L-band loop EDFA through C-band signal injection. IEEE Photonics Technology Letters, 17(7), 1402–1404. Citations: 27

Basgumus, A., Durak, F. E., Altuncu, A., & Yilmaz, G. (2015). A universal and stable all-fiber refractive index sensor system. IEEE Photonics Technology Letters, 28(2), 171–174. Citations: 26

Umakoglu, I., Namdar, M., Basgumus, A., Kara, F., Kaya, H., & Yanikomeroglu, H. (2021). BER performance comparison of AF and DF assisted relay selection schemes in cooperative NOMA systems. In Proceedings of the 2021 IEEE International Black Sea Conference on Communications and Networking. Citations: 22