Yuekun Yang | Cloud Computing | Innovative Research Award

Innovative Research Award

Yuekun Yang
Nanjing University,China

Yuekun Yang
Affiliation Nanjing University
Country China
Scopus ID 57203690382
Documents 26
Citations 677
h-index 10
Subject Area Cloud Computing
Event Computer Scientists Awards
Google Scholar 3xNlTekAAAAJ&hl

Yuekun Yang is a researcher affiliated with Nanjing University whose work spans intelligent sensing, photosensors, optical computing, low-dimensional materials, and emerging information technologies. His scholarly contributions have focused on the development of advanced sensing architectures and novel electronic and optoelectronic devices capable of supporting future intelligent computing systems. Through interdisciplinary research that integrates materials science, electronics, and computational technologies, Yang has contributed to advancements relevant to cloud-enabled intelligent infrastructures and next-generation information processing platforms.[1]

Abstract

This article summarizes the academic profile and research achievements of Yuekun Yang. His work emphasizes intelligent machine vision, advanced photosensing technologies, two-dimensional materials, and optoelectronic systems. Through contributions to high-impact scientific publications and collaborative research projects, he has participated in the development of innovative sensing and computing paradigms that support future information technologies and intelligent systems.[2]

Keywords

Intelligent Sensing, Photosensors, Optical Computing, Two-Dimensional Materials, Machine Vision, Cloud Computing, Optoelectronics, Information Technology, Phototransistors, Nanomaterials.

Introduction

The evolution of intelligent computing systems increasingly depends on advanced sensing technologies and efficient information-processing architectures. Yuekun Yang has contributed to this field by investigating innovative material platforms and device structures that integrate sensing, computation, and communication capabilities. His research aligns with emerging trends in artificial intelligence hardware, intelligent vision systems, and scalable electronic integration.[3]

Research Profile

Yang’s research interests encompass intelligent sensing, photosensors, optical computing, and low-dimensional electronic materials. His scholarly record includes 26 indexed publications with 677 citations and an h-index of 10. His work demonstrates a multidisciplinary approach combining device engineering, materials science, and information technologies to address challenges in future computing and sensing platforms.[1]

Research Contributions

  • Contributed to graphene-assisted metal transfer printing for wafer-scale integration of metal electrodes and two-dimensional materials.
  • Participated in the development of in-sensor dynamic computing systems for intelligent machine vision applications.
  • Advanced understanding of two-dimensional materials and their prospects in future information technology.
  • Contributed to nonvolatile van der Waals heterostructure phototransistors for encrypted optoelectronic logic circuits.
  • Supported development of ultrathin dielectric materials for high-performance field-effect transistor technologies.

Publications

  • Graphene-assisted metal transfer printing for wafer-scale integration of metal electrodes and two-dimensional materials (Nature Electronics, 2022).
  • In-sensor dynamic computing for intelligent machine vision (Nature Electronics, 2024).
  • Two-dimensional materials for future information technology: status and prospects (Science China Information Sciences, 2024).
  • Nonvolatile van der Waals heterostructure phototransistor for encrypted optoelectronic logic circuit (ACS Nano, 2022).
  • Ultrathin Van der Waals lanthanum oxychloride dielectric for 2D field-effect transistors (Advanced Materials, 2025).

Research Impact

The citation performance of Yang’s publications reflects substantial academic visibility within the fields of materials science, electronics, and intelligent sensing. His research has contributed to ongoing discussions concerning future computing architectures, integrated sensing systems, and optoelectronic device innovation. Several publications have appeared in internationally recognized journals, indicating broad scholarly engagement and scientific relevance.[4]

Award Suitability

Yuekun Yang’s research portfolio demonstrates originality, interdisciplinary collaboration, and measurable scientific impact. His contributions to intelligent sensing, optical computing, and advanced materials align with the objectives of the Innovative Research Award. The combination of influential publications, citation performance, and technological relevance supports recognition within the Computer Scientists Awards framework.[5]

Conclusion

Yuekun Yang has established a research profile centered on intelligent sensing technologies, advanced electronic materials, and machine vision systems. His scholarly activities contribute to emerging directions in information technology and optoelectronics, providing a foundation for future innovations in intelligent computing and integrated sensing platforms.[6]

References

  1. Elsevier. (n.d.). Scopus author details: Yuekun Yang, Author ID 57203690382. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57203690382
  2. Yang, Y. et al. (2024). In-sensor dynamic computing for intelligent machine vision. Nature Electronics.
    https://www.nature.com/articles/s41928-024-01124-0
  3. Qiu, H. et al. (2024). Two-dimensional materials for future information technology: status and prospects. Science China Information Sciences.
    https://link.springer.com/article/10.1007/s11432-024-4033-8
  4. Liu, G. et al. (2022). Graphene-assisted metal transfer printing for wafer-scale integration of metal electrodes and two-dimensional materials. Nature Electronics.
    https://link.springer.com/article/10.1007/s11432-024-4033-8
  5. Wang, S. et al. (2022). Nonvolatile van der Waals heterostructure phototransistor for encrypted optoelectronic logic circuit. ACS Nano.
    https://pubs.acs.org/doi/abs/10.1021/acsnano.1c10978
  6. Li, L. et al. (2025). Ultrathin Van der Waals lanthanum oxychloride dielectric for 2D field-effect transistors. Advanced Materials.
    https://advanced.onlinelibrary.wiley.com/doi/abs/10.1002/adma.202309296

Mahfooz Alam | Cloud Computing | Best Researcher Award

Assist. Prof. Dr. Mahfooz Alam | Cloud Computing | Best Researcher Award

Assistant professor, G. L. Bajaj College of Technology and Management, Greater Noida, India

Dr. Mahfooz Alam is an esteemed academician and researcher in the field of Computer Science, specializing in Cloud Computing, Internet of Things (IoT), Workflow Scheduling, and Machine Learning ๐Ÿค–. He is currently serving as an Assistant Professor in the Department of MCA at G. L. Bajaj College of Technology and Management, Greater Noida, India ๐Ÿ‡ฎ๐Ÿ‡ณ. With a strong academic background and years of teaching experience, Dr. Alam is dedicated to advancing knowledge in secured workflow allocation and innovative computing methodologies. His research contributions are well-recognized, with publications in reputed journals, including IEEE, Springer, Elsevier, and Wiley ๐Ÿ“š.

Publication Profile

Google Scholar

๐ŸŽ“ Education

Dr. Mahfooz Alam holds a Ph.D. in Computer Science from Aligarh Muslim University (AMU), Aligarh, India ๐ŸŽ“. He pursued his M.Tech. in Computer Science and Engineering from Dr. A. P. J. Abdul Kalam Technical University, Lucknow. Additionally, he completed his B.C.A. and M.C.A. from Indira Gandhi National Open University (IGNOU), New Delhi. His academic journey reflects his commitment to excellence in research and innovation in computing technologies ๐Ÿ–ฅ๏ธ.

๐Ÿ’ผ Experience

Dr. Alam has a wealth of teaching and research experience, having served as an Assistant Professor at Al-Barkaat College of Graduate Studies (ABCGS), Aligarh, for six years ๐Ÿซ. Currently, he holds the position of Assistant Professor at G. L. Bajaj College of Technology and Management, Greater Noida. His dedication to mentoring students and contributing to research has made him a respected figure in academia. His expertise extends to cutting-edge domains such as heuristic and meta-heuristic approaches in secured workflow allocation ๐Ÿ”ฌ.

๐Ÿ† Awards and Honors

Dr. Mahfooz Alam has been recognized for his significant contributions to computer science research. His work has been published in high-impact international journals and conferences, gaining citations and recognition from fellow researchers worldwide ๐ŸŒ. His contributions to machine learning applications and cloud computing security have positioned him as a thought leader in the field.

๐Ÿ”ฌ Research Focus

Dr. Alam’s research primarily focuses on Cloud Computing, IoT, Workflow Scheduling, and Load Balancing โ˜๏ธ. He explores innovative approaches to software defect prediction, cybersecurity in IoT, and machine learning-driven optimization techniques. His research integrates heuristic, meta-heuristic, and reinforcement learning methods to address challenges in secure computing environments ๐Ÿ”.

๐Ÿ”š Conclusion

Dr. Mahfooz Alam is a dedicated academician and researcher contributing extensively to cloud computing, machine learning, and IoT security. His publications, teaching, and research endeavors continue to impact the field, shaping innovative solutions for complex computational challenges ๐Ÿš€. With a strong passion for advancing knowledge and technology, Dr. Alam remains a prominent figure in the global research community ๐ŸŒ.

๐Ÿ“œ Publications

Comprehensive Bibliographic Survey and Forward-Looking Recommendations for Software Defect Prediction (IEEE Access, 2025) ๐Ÿ“– DOI: 10.1109/ACCESS.2024.3517419

Software Defects Prediction Using Generative Adversarial Network Based Data Balancingย (Book Chapter, 2025) ๐Ÿ“– DOI: 10.1007/978-3-031-83790-6_22

Reinforcing Defect Prediction: A Reinforcement Learning Approach ย (Iran Journal of Computer Science, 2025) ๐Ÿ“– DOI: 10.1007/s42044-024-00214-8

Ensemble Deep Learning Techniques for Time Series Analysisย (Cluster Computing, 2025) ๐Ÿ“– DOI: 10.1007/s10586-024-04684-0

A Levelized Multiple Workflow Heterogeneous Earliest Finish Time Allocation Model ย (Algorithms, 2025) ๐Ÿ“– DOI: 10.3390/a18020099

Cybersecurity Challenges for Social, Ad-hoc, and Sensor Networks in IoT ย (Wireless Ad-hoc and Sensor Networks, 2024) ๐Ÿ“– DOI: 10.1201/9781003528982-12

Performance Evaluation on Detection of Phishing Websites Using Machine Learning Techniquesย (ICEECT, 2024) ๐Ÿ“– DOI: 10.1109/iceect61758.2024.10739275

Empowering IoT Security (Book Chapter, 2024) ๐Ÿ“– DOI: 10.1201/9781003460367-11

A Trustworthy Hybrid Model for Transparent Software Defect Prediction: SPAM-XAIย (PLOS ONE, 2024) ๐Ÿ“– DOI: 10.1371/journal.pone.0307112

Security Challenges for Workflow Allocation Model in Cloud Computing Environment: A Comprehensive Survey, Framework,
Taxonomy, Open Issues, and Future Directions
ย (Journal of Supercomputing, 2024) ๐Ÿ“– DOI: 10.1007/s11227-023-05873-1