Yuekun Yang | Cloud Computing | Innovative Research Award

Published on by Computer Scientists Awards

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

Mr. John de Britto Chinnappan | Computer Science | Editorial Board Member

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Mr. John de Britto Chinnappan | Computer Science | Editorial Board Member

Saveetha Engineering College| India

Dr. C. John De Britto is a dedicated researcher in Electrical and Electronics Engineering with a strong focus on power electronics, renewable energy systems, electric drives, optimization algorithms, and intelligent control strategies. His research work explores innovative solutions for improving power quality, enhancing the efficiency of renewable energy integration, and advancing smart energy systems. With contributions spanning image enhancement techniques, hybrid renewable systems, DC–DC converter architectures, electric vehicle impact mitigation, and intelligent control for photovoltaic systems, he brings a multidisciplinary approach bridging conventional power engineering with modern computational intelligence. His scholarly output includes 14 Scopus-indexed documents that have collectively received 40 citations with an h-index of 4 on Scopus. Additionally, his Google Scholar profile reflects 50 citations, an h-index of 4, and an i10-index of 1, highlighting the growing influence and visibility of his work. His publications demonstrate a strong commitment to developing sustainable engineering solutions, especially in areas such as quasi Z-source converters, hybrid renewable energy design, embedded platforms, fault recognition in industrial motors, and bio-inspired optimization for control systems. Dr. De Britto’s research impact is evident across peer-reviewed journals, international conferences, and interdisciplinary collaborations, with several studies addressing modern challenges such as electric vehicle charging impacts, microgrid performance, and automation for safety-critical applications. His continuous contributions to energy systems, computational approaches, and power conversion technologies position him as an emerging academic voice in renewable and intelligent power engineering research.

Profile

Scopus | ORCID | Google Scholar

Featured Publications

Venkatesh, S., De Britto, C. J., Subhashini, P., & Somasundaram, K. (2022). Image enhancement and implementation of CLAHE algorithm and bilinear interpolation. Cybernetics and Systems, 1–13.

Pradeep, M., Sathishkumar, S., & Subramanian, A. T. S. (2019). Recognition of fault and security of three phase induction motor by means of programmable logic controller. IOP Conference Series: Materials Science and Engineering, 623, 012017.

Yuvaraj, T., Prabaharan, N., De Britto, C. J., Thirumalai, M., Salem, M., & others. (2024). Dynamic optimization and placement of renewable generators and compensators to mitigate electric vehicle charging station impacts using the spotted hyena optimization algorithm. Sustainability, 16(19), 8458.

De Britto, C. J., Nagarajan, S., & Kumar, R. S. (2023). Effective design and implementation of hybrid renewable system using convex programming. International Journal of Green Energy, 20(13), 1473–1487.

De Britto, C. J., & Nagarajan, S. (2018). High performance quasi Z-source resonant converter with hybrid energy resources for rural electrification. International Journal of Engineering and Advanced Technology, 8(2C2), 132–135.

Obsa Gilo Wakuma | Computer Science | Best Researcher Award

Published on by Computer Scientists Awards

Dr. Obsa Gilo Wakuma | Computer Science | Best Researcher Award

Ass. Prof, Wallaga University, Ethiopia

Dr. Obsa Gilo Wakuma is a dedicated computer scientist specializing in deep learning and domain adaptation. With extensive experience in academia, he has contributed significantly to the field through his research and teaching. Dr. Obsa has held various positions at Wallaga University, Ethiopia, and currently serves as a research scholar at the Indian Institute of Technology Patna, India. His expertise spans multiple programming languages and database management systems, making him a versatile and valuable contributor to the field of computer science.

Profile

Strengths for the Award:

  1. Extensive Research Background: Dr. Obsa Gilo has a robust academic background, culminating in a Ph.D. in Computer Science and Engineering with a focus on deep learning approaches for efficient domain adaptation. His research in domain adaptation, particularly in sensor data and image classification, showcases his innovative contributions to the field.
  2. Publications: Dr. Gilo has a significant number of publications in reputed journals and conference proceedings. Notable among them are:
    • “Kernel bures metric for domain adaptation in sensor data” in Expert System with Applications (2024)
    • “Subdomain adaptation via correlation alignment with entropy minimization for unsupervised domain adaptation” in Pattern Analysis and Applications (2024)
    • “Rdaot: Robust unsupervised deep sub-domain adaptation through optimal transport for image classification” in IEEE Access (2023)
  3. Teaching and Mentoring: His employment history includes roles such as Lecturer and Graduate Assistant at Wallaga University, demonstrating his commitment to education and mentoring the next generation of scholars.
  4. Skills and Competencies: Dr. Gilo possesses strong technical skills in various programming languages, databases, and web development technologies, along with proficiency in English, Afaan Oromoo, and Amharic. This multilingual ability enhances his capacity to engage with diverse communities.
  5. Community Service: His experience includes academic research, teaching, training, consultation, and community service, reflecting a well-rounded professional dedicated to both academic and societal contributions.

Areas for Improvement:

  1. Practical Community Impact: While Dr. Gilo has an impressive academic and research portfolio, there could be more emphasis on the practical application of his research directly benefiting local communities. Highlighting specific projects or initiatives where his work has directly impacted community development would strengthen his case.
  2. Collaboration with Local Institutions: Greater collaboration with local institutions and involvement in projects addressing community-specific issues could further enhance his profile. Establishing partnerships with local universities, NGOs, or governmental bodies to implement his research findings in real-world settings would be beneficial.
  3. Visibility and Outreach: Increasing the visibility of his work through public lectures, community workshops, or outreach programs can help in demonstrating the broader societal impact of his research. Engaging with the community through these platforms can showcase the practical benefits of his research.

 

Education: 🎓

Dr. Obsa Gilo Wakuma holds a Ph.D. in Computer Science and Engineering from the Indian Institute of Technology Patna, with a thesis on “Deep Learning Approaches for Efficient Domain Adaptation.” He earned his M.Sc. in Computer Science from Wallaga University, where he developed an Information Extraction Model for Afaan Oromo news texts. Dr. Obsa also holds a B.Sc. in Computer Science from Wallaga University and has a strong foundation from Sibu Sire Preparatory and High School.

Experience: 💼

Dr. Obsa’s professional journey includes roles such as Recorder and Laboratory Technician at Wallaga University. He progressed to become a Graduate Assistant, Lecturer, and finally a Research Scholar at IIT Patna. His career reflects a blend of administrative, technical, and academic responsibilities, showcasing his diverse skill set and commitment to the field.

Research Interests: 🔍

Dr. Obsa’s research interests lie in deep learning, domain adaptation, and unsupervised learning. He has focused on developing efficient methods for domain adaptation in sensor data and image classification, contributing to several high-impact publications. His work aims to enhance the applicability and robustness of machine learning models in diverse environments.

Awards: 🏆

Dr. Obsa has been recognized for his academic excellence and research contributions throughout his career. He has received accolades for his innovative work in domain adaptation and deep learning, highlighting his role as a prominent researcher in the field of computer science.

Publications

  1. Unsupervised Sub-Domain Adaptation Using Optimal Transport. Journal of Visual Communication and Image Representation, 94, 103857. Cited by: 1 article.
  2. Kernel Bures Metric for Domain Adaptation in Sensor Data. Expert System with Applications, 255(Part C), 124725. Cited by: 1 article.
  3. Subdomain Adaptation via Correlation Alignment with Entropy Minimization for Unsupervised Domain Adaptation. Pattern Analysis and Applications, 27(1), 13. Cited by: 1 article.
  4. RDAOT: Robust Unsupervised Deep Sub-Domain Adaptation through Optimal Transport for Image Classification. IEEE Access. Cited by: 1 article.
  5. Integration of Discriminate Features and Similarity Preserving for Unsupervised Domain Adaptation. In 2022 IEEE 19th India Council International Conference (INDICON), pp. 1–6. Cited by: 1 article.

 

Vijaya bhaskar Sadu | Cloud Computing | Cloud Computing Achievement Award

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Mr. Vijaya bhaskar Sadu | Cloud Computing | Cloud Computing Achievement Award

Cloud Architect, JNTU Kakinada/ Software Engineer in USA, United States

Vijaya Bhaskar Sadu is an accomplished Cloud Data Architect at Wellsfargo Bank, USA. With over 20 years of experience in IT, he has significantly contributed to the fields of Robotics, Artificial Intelligence, Cloud Computing, Big Data, and Web Technologies. His work has garnered recognition through numerous patents, peer-reviewed journal publications, and books.

Profile

Google Scholar

 

Education 📚

Vijaya Bhaskar Sadu earned his B.Tech degree in Mechanical Engineering with distinction from JNTU Kakinada. He further pursued an M.S. in Robotics & Artificial Intelligence, also with distinction, from IIT Madras. Currently, he is a Ph.D. candidate specializing in Artificial Intelligence and Machine Learning.

Experience 💼

With two decades of experience in the IT industry, Vijaya Bhaskar Sadu has established himself as a seasoned professional and researcher. His role as a Cloud Data Architect at Wellsfargo Bank involves leveraging his expertise to innovate and optimize cloud technologies and data management solutions.

Research Interests 🔍

His primary research interests include Robotics, Artificial Intelligence, Cloud Computing, Big Data, and Web Technologies. He has been actively involved in advancing these fields through his research projects, publications, and patents.

Awards 🏆

Vijaya Bhaskar Sadu’s contributions have been recognized with several accolades. He has published 15 peer-reviewed journal articles, authored three books, and holds six patents. His work continues to make a significant impact on the fields of cloud technologies and AI.

Publications

Robotics and AI Integration in Cloud Computing – Published in Journal of Cloud Computing, 2021, cited by 15 articles.

Big Data Analytics in Financial Services – Published in International Journal of Big Data, 2020, cited by 10 articles.

Advancements in Web Technologies – Published in Web Technologies Journal, 2019, cited by 8 articles.