Mr. Xinwei He – Object Detection – Best Researcher Award

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Mr. Xinwei He - Object Detection - Best Researcher Award

Foshan University - China

Author Profile

GOOGLE SCHOLAR

Summary


Xinwei He, a second-year master’s student in software engineering at foshan university, is an emerging researcher in the field of object detection with a strong inclination toward real-world applications in power electronics and automation systems. his key contribution—tgcpn: two-level grid context propagation network for 3d small object detection—showcases a blend of academic depth and practical insight. through active participation in publication, code sharing, and peer-reviewed processes, xinwei is steadily building a credible academic presence. while early in his career, his focused research direction and commitment to quality reflect significant potential for future impact.

Early academic pursuits


Xinwei he is currently a second-year master's student in software engineering at foshan university. with a foundational understanding of computational models and a growing proficiency in research methodology, xinwei began contributing to the academic domain early in postgraduate studies. the integration of power Object Detection electronics principles with intelligent object recognition marked a turning point in xinwei's academic direction. xinwei is steadily building a credible academic presence. while early in his career, his focused research direction and commitment to quality reflect significant potential for future impact.

Professional endeavors


Though still in the academic phase, xinwei he has demonstrated professional maturity through the successful development of the project titled tgcpn: two-level grid context propagation network for 3d small object detection. this work highlights the Object Detection application of computer vision within high-efficiency environments, including power electronics-based automation systems. the project underscores a capacity to work at the intersection of deep learning and real-world utility.

Contributions and research focus


Xinwei’s primary area of research is object detection, with an emphasis on small-scale 3d object identification in complex environments. the recently completed paper revision and response to peer review comments demonstrates not only technical proficiency but also academic resilience. this effort contributes meaningfully to current advancements Object Detection in image detection technologies within power electronics and robotics-based systems.

Impact and influence


Xinwei he's ongoing work is gaining attention through platforms like github and springer. by leveraging code sharing and academic publication, Xinwei is establishing a transparent and collaborative research footprint. Object Detection although citation indices are in early stages, the methodological rigor and thematic relevance suggest promising growth in academic influence, particularly in the automation sector.

Academic cites


The project has been recognized in academic channels, with a publication under a reputable journal indexed by springer. while specific citation metrics are pending, xinwei's engagement with high-impact areas such as Object Detection power electronics-driven automation systems, signal propagation, and detection architecture indicates future relevance in citations and scholarly reference.

Legacy and future contributions


Xinwei he is poised to contribute further to the fields of object detection and robotics. future plans likely include expanding research collaborations, deepening the interface between object detection and applied power electronics, and increasing journal presence. with a strong ethical foundation as expressed in the self-declaration, xinwei seeks to build a legacy of integrity, innovation, and interdisciplinary growth.

Notable Publications

Title: Tgcpn: Two-level grid context propagation network for 3D small object detection
Authors: Y. Zhou, L. Pu, X. Xu, C. Yi, X. He, Y. Zhou, Y. Xu
Journal: Pattern Analysis and Applications

Conclusion


Xinwei He exemplifies the qualities of a dedicated and innovative researcher whose early contributions are already aligning with critical technological trends like automation and power electronics-driven systems. his consistent efforts in refining research output, responding to scholarly critique, and collaborating through open platforms position him well for long-term influence. with continued mentorship and engagement, xinwei is set to evolve into a valuable contributor to the global robotics and software engineering community.

 

Mr. Huixian Lin – Deep Learning – Best Researcher Award

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Mr. Huixian Lin - Deep Learning - Best Researcher Award

Guangdong Ocean University - China

Author Profile

SCOPUS

Summary

Mr. Huixian Lin is a dedicated full-time teacher at Guangdong Ocean University with a master's degree in Computer Science and Technology. His academic focus lies in image processing, machine learning, and the integration of power electronics in intelligent systems. He has made notable contributions, including enhancing the YOLOv5s model for degraded image detection and publishing three SCI-indexed research papers. His teaching and research work reflects a commitment to advancing practical, AI-driven solutions in real-world environments.

Early academic pursuits

Mr. Huixian Lin began his academic journey with a strong inclination toward computational sciences. His commitment to technological excellence led him to pursue a Master of Science degree in Computer Science and Technology from Guangdong Ocean University, completed in 2023. During his academic training, he cultivated a keen interest in image processing, deep learning machine learning, and system optimization. His foundational knowledge in applied mathematics, algorithms, and power electronics laid a strong base for future research and teaching.

Professional endeavors

Since 2023, Mr. Lin has been serving as a full-time teacher at the College of Mathematics and Computer Science, Guangdong Ocean University. His teaching methodology emphasizes practical applications of theoretical concepts, especially in areas like deep learning intelligent systems and computer vision. In his short tenure, he has made significant strides in mentoring undergraduate students and guiding them through hands-on research in modern computing fields, including power electronics applications in automation systems.

Contributions and research focus

Mr. Lin’s most notable academic contribution is his proposed improvement of the YOLOv5s model, targeting enhanced detection of degraded images—a challenge in both surveillance and industrial inspection sectors. His research integrates advanced machine learning with classical image processing techniques. He has authored 3 SCI-indexed papers in reputed journals, deep learning showcasing innovations that have practical implications in smart sensing, automation, and power electronics interface systems. These contributions reflect a commitment to solving real-world problems using intelligent technology frameworks.

Impact and influence

Mr. Lin's work has been recognized within academic circles for its technical accuracy and applicability. His adaptations to image recognition models have improved reliability in noisy environments, offering benefits to sectors like security surveillance, medical diagnostics, and automated inspection systems. As a young academic, deep learning his influence is growing, especially among peers focusing on embedded systems, AI algorithms, and sensor-integrated power electronics.

Academic citations

Although at an early stage of his academic journey, Mr. Lin's publications have begun to attract citations in related research fields. His work is cited for contributions to degraded image classification, neural network efficiency optimization, deep learning and algorithm adaptability in constrained environments. This emerging scholarly attention suggests a promising trajectory in the years ahead.

Legacy and future contributions

Looking ahead, Mr. Lin aspires to build a legacy in the intersection of artificial intelligence, image processing, and real-time computing. He aims to extend his research toward more adaptive and energy-efficient machine learning models with industrial deployment in mind. His future contributions are likely to focus on smarter integration of visual data into automated decision-making systems, deep learning particularly where power electronics and AI co-evolve. Through his ongoing role at Guangdong Ocean University, he is poised to nurture future innovators and push the boundaries of applied computing.

Notable Publications

Effective superpixel sparse representation classification method with multiple features and L 0smoothing for hyperspectral images.

Conclusion

In the early stages of his academic career, Mr. Huixian Lin has already made a meaningful impact through research and instruction. His innovative approach to machine learning and image recognition, especially when combined with power electronics, positions him as a promising figure in the field. With a growing scholarly presence and a passion for technological development, Mr. Lin is set to contribute significantly to the future of smart computing and interdisciplinary research.

Mr. Abubakar Adamu – Computer Science and Artificial Intelligence – Best Paper Award

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Mr. Abubakar Adamu - Computer Science and Artificial Intelligence - Best Paper Award

Federal University of Technology Minna Nigeria and University of Malaya - Malaysia

Author Profile

ORCID

Summary

Adamu Abubakar is an emerging researcher and academic with a strong foundation in computer science, artificial intelligence, and telecommunications. his educational background, which includes a master's degree with distinction and an ongoing phd, reflects his dedication to academic excellence and technical mastery. professionally, he has blended academic teaching with significant industry experience at leading telecom firms, giving him a well-rounded perspective on both theoretical and practical aspects of technology.

His research interests focus on the integration of artificial intelligence into telecommunication systems, with a growing emphasis on the role of power electronics in optimizing network infrastructure and improving service delivery. his involvement in global research networks like vodan demonstrates his commitment to using technology for societal benefit.

Early academic pursuits

Adamu Abubakar began his academic journey with a bachelor’s degree in computer science from usman danfodio university sokoto, nigeria, where he laid a solid foundation in computing principles and information technology. his pursuit of excellence continued with a master of technology (m.tech) in computer science at the federal university of technology minna, where he graduated with distinction. Computer Science and Artificial Intelligence his master's thesis focused on developing an enhanced self-service software model tailored for the nigerian telecommunication sector, integrating concepts applicable in power electronics systems through efficient data processing and control mechanisms.

Currently, he is enrolled in a phd program in computer science and artificial intelligence at the federal university of technology minna. additionally, he has undertaken a phd mobility attachment program at the university of malaya, malaysia, further expanding his exposure to global research practices. he also holds a postgraduate diploma in education from the national teachers institute, reflecting his dedication to academic mentorship and teaching excellence.

Professional endeavors

Adamu Abubakar's professional career is marked by significant teaching, research, and managerial responsibilities. he presently serves as a lecturer i at ibrahim badamasi babangida university, lapai, where he teaches courses such as data communication, networking, artificial intelligence, and computer architecture. he actively supervises final-year projects, providing guidance that connects theoretical concepts with practical applications, including emerging technologies such as power electronics in telecommunication systems.

Prior to his academic role, he accumulated valuable industry experience at leading telecommunication firms in nigeria, including mtn nigeria limited and zain nigeria limited. Computer Science and Artificial Intelligence his positions in customer service and distribution management honed his leadership, technical, and organizational skills, critical in both corporate operations and academic settings.

Contributions and research focus

Adamu Abubakar’s research interests lie primarily in artificial intelligence and telecommunication technologies. his academic and industry experiences have positioned him to explore intelligent systems design, network optimization, Computer Science and Artificial Intelligence and data-driven solutions to enhance telecom services. he also emphasizes the potential applications of power electronics in smart grid communication systems and energy-efficient telecommunication infrastructure.

As a data steward in the virus outbreak data network (vodan) africa & asia covid-19 volunteer network, he contributed to data management and system analysis, reinforcing his commitment to impactful scientific research.

Impact and influence

Adamu Abubakar’s dual expertise in academia and the telecommunications industry allows him to bridge the gap between theoretical knowledge and practical solutions. his teaching impacts undergraduate and postgraduate students, inspiring the next generation of nigerian computer scientists. Computer Science and Artificial Intelligence his involvement in technological research related to artificial intelligence and power electronics has the potential to shape more efficient telecom and computing infrastructures in africa and beyond.

Academic cites

Adamu Abubakar’s master's thesis on enhanced self-service models for nigerian telecom networks remains a relevant citation for researchers developing customer-oriented software systems in developing regions. ongoing collaborations through his phd programs and attachments are expected to yield publications contributing to fields like machine learning, Computer Science and Artificial Intelligence network optimization, and the integration of power systems and power electronics in information technology.

Legacy and future contributions highlight

With a vision focused on blending artificial intelligence with telecommunication advancements, adamu abubakar aims to make long-lasting contributions to nigeria’s digital infrastructure. he is committed to further exploring the synergy between ai-driven network systems and power electronics, ensuring sustainable, energy-efficient, and intelligent telecom solutions. Computer Science and Artificial Intelligence his legacy will likely include not only scholarly publications but also the cultivation of students and professionals well-versed in next-generation technologies.

Notable Publications

  1. Title: Systematic literature review and bibliometric analysis of pipeline monitoring and leakage detection techniques
    Authors: Adamu Abubakar; Opeyemi Aderiike Abisoye; Isiaq Oludare Alabi; Adepoju Solomon; Ishaq Oyebisi Oyefolahan
    Journal: Discover Mechanical Engineering

  1. Title: Exploring the Integration of a Patient Generated Health Data in a FAIR Digital Health System in Low-Resourced Settings: A User-Centered Approach
    Authors: Abdullahi Abubakar Kawu; Rens Kievit; Adamu Abubakar; Mirjam Van Reisen; Dympna O'Sullivan; Lucy Hederman
    Conference: ACM International Conference (Proceedings)

Conclusion

Adamu Abubakar's career trajectory showcases a harmonious balance of teaching, research, and industrial practice. his expertise positions him to make impactful contributions to the fields of ai-driven telecommunication systems and power electronics applications in emerging markets. looking ahead, he is set to influence the development of energy-efficient, intelligent technologies that will shape nigeria's digital future and inspire the next generation of tech innovators.