Assoc. Prof. Dr. Mingfeng Lu | Computer Vision | Research Excellence Award

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Assoc. Prof. Dr. Mingfeng Lu | Computer Vision | Research Excellence Award

Beijing Institute of Technology | China

Assoc. Prof. Dr. Mingfeng Lu is a Senior Laboratory Technician and Associate Professor at the School of Integrated Circuit and Electronics, Beijing Institute of Technology. He earned his BS and MS degrees in electronics engineering and circuits and systems from BIT, and a PhD in optical engineering. His research focuses on optical metrology, monocular visual measurement, and the application of modern signal processing and artificial intelligence techniques, including fractional Fourier transform, chirp Fourier transform, computer vision and deep learning. He has published extensively in SCI-indexed journals, holds multiple patents, and serves as a core member and co-principal investigator on national and municipal research projects.

Citation Metrics (Scopus)

240
180
120
60
0

Citations
225

Documents
58

h-index
8

Citations

Documents

h-index


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Featured Publications

Mr. Murtaza Hussain | Vision Language Model | Research Excellence Award

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Mr. Murtaza Hussain | Vision Language Model | Research Excellence Award

Kumoh National Institute of Technology | South Korea

Murtaza Hussain is a Master’s student in IT Convergence Engineering at Kumoh National Institute of Technology, South Korea, and a Research Assistant at the WENS Lab specializing in deep learning, computer vision, and ROS2-based systems. His research focuses on 2D/3D object detection and segmentation, vision–language models, multi-modal learning, Vision Language Model and edge AI deployment on Jetson devices. He has developed real-time AI solutions for cardiac ultrasound analysis, smart farming with UxV swarms, industrial inspection, and safety monitoring, achieving high accuracy and real-time performance. Murtaza is the first author of accepted international journal and conference papers, including works in Neurocomputing and ICUFN, and has ongoing submissions to the IEEE Internet of Things Journal.

Citation Metrics (Scopus)

3
2.25
1.5
0.75
0

Citations
1

Documents
3

h-index
1

Citations

Documents

h-index


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Featured Publication

Dr. Faisal Saeed | Object Detection | Excellence in Research Award

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Dr. Faisal Saeed | Object Detection | Excellence in Research Award

Shenzhen University | China

Dr. Faisal Saeed is an ai research scientist specializing in computer vision, deep learning, and intelligent manufacturing, with a strong research portfolio built through advanced academic training and international research appointments. He earned his master’s combined Ph.d. in computer science from Kyungpook National University, South Korea, where his work focused on transformer-based architectures for industrial small-object detection, culminating in the thesis feature enhanced assignment-based detection transformer for industrial small object detection. His academic contributions include 21 documents, a growing research footprint of 738 citations, and an h-index of 10, reflecting the global impact of his work across ai-driven automation, defect detection, and predictive maintenance. Professionally, he has served as a university research assistant and later as a postdoctoral fellow in both South Korea and China, contributing to deep learning theory, medical image analysis, multimodal ai, Object Detection and industrial visual inspection systems. His research integrates digital twins, time-series forecasting, and transformer models to advance intelligent manufacturing and robotics. Committed to bridging theoretical innovation with real-world applications, Dr. Saeed continues to publish influential work, secure funding for emerging ai research, and contribute to the scientific community through teaching, collaboration, and cutting-edge industrial ai development.

Profile: Scopus | Google Scholar

Featured Publications

Shah, H. A., Saeed, F., Yun, S., Park, J. H., Paul, A., & Kang, J. M. (2022). A robust approach for brain tumor detection in magnetic resonance images using finetuned EfficientNet. IEEE Access, 10, 65426–65438.

Saeed, F., Paul, A., Rehman, A., Hong, W. H., & Seo, H. (2018). IoT-based intelligent modeling of smart home environment for fire prevention and safety. Journal of Sensor and Actuator Networks, 7(1), 11.

Saeed, F., Paul, A., Karthigaikumar, P., & Nayyar, A. (2020). Convolutional neural network based early fire detection. Multimedia Tools and Applications, 79(13), 9083–9099.

Saeed, F., Ahmed, M. J., Gul, M. J., Hong, K. J., Paul, A., & Kavitha, M. S. (2021). A robust approach for industrial small-object detection using an improved faster regional convolutional neural network. Scientific Reports, 11(1), 23390.

Rehman, A., Rathore, M. M., Paul, A., Saeed, F., & Ahmad, R. W. (2018). Vehicular traffic optimisation and even distribution using ant colony in smart city environment. IET Intelligent Transport Systems, 12(7), 594–601.

Mr. Yasuyuki Ihara – Image Recognition – Best Researcher Award

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Mr. Yasuyuki Ihara - Image Recognition - Best Researcher Award

NEC Solution Innovators, Ltd. - Japan

Author Profile

SCOPUS

Summary

Yasuyuki Ihara is a versatile researcher at nec solution innovators, ltd., with a strong academic background in mathematics from Nagoya university. his professional journey spans cryptographic systems, machine learning, image recognition, and the integration of quantum computing into real-world applications. notable contributions include a cyber-physical system for urban transportation and multiple industry-led projects focused on image analysis, quantum feasibility, and cryptographic evaluation. his citation metrics, though modest, reflect sustained research across diverse fields. keywords like power electronics highlight the interdisciplinary relevance of his work in current and future technology domains.

Early academic pursuits

Yasuyuki Ihara began his academic journey with a strong foundation in mathematics, earning a master’s degree from nagoya university. during this period, his academic curiosity gravitated toward theoretical constructs, particularly in cryptographic systems. his early studies laid a solid groundwork for exploring complex mathematical frameworks which would later influence his contributions in emerging technologies such as Image Recognition quantum computing and power electronics.

Professional endeavors

Ihara currently serves as a researcher at nec solution innovators, ltd., where he has evolved across multiple technical domains in alignment with organizational strategy. initially rooted in cryptography—including hyperelliptic curve cryptography—his career expanded to Image Recognition embrace machine learning and image recognition systems. this shift demonstrated both his versatility and his ability to contribute to dynamic, technology-driven industry sectors, such as smart infrastructure and power electronics systems.

Contributions and research focus

Ihara’s research centers around bridging mathematical theory with real-world applications. a major achievement includes the development of a cyber-physical system for urban transportation empowered by quantum computing, a project combining his Image Recognition expertise in both cryptography and advanced computing. his work continues to push boundaries in integrating quantum algorithms into machine learning pipelines, with potential applications in intelligent transport systems, security protocols, and power electronics optimization.

Impact and influence

His collaborative efforts have resulted in three significant industry-backed projects: field analyst™ image recognition project, quantum computing feasibility study for transport network systems, cryptographic systems evaluation using hyperelliptic curve cryptography. These projects highlight his ability to merge theoretical research with Image Recognition industrial applications, influencing strategic directions at nec and beyond. his adaptability across fields makes him a key contributor in interdisciplinary technological advancement.

Academic cites

Yasuyuki Ihara has built a modest yet meaningful citation record over a 14-year period (2010–2024), reflecting the specialized and evolving nature of his work: google scholar citations, h-index, i10-index. These figures signify sustained scholarly engagement, Image Recognition especially considering his shift across various emerging domains like quantum computing, machine learning, and power electronics.

Legacy and future contributions

Ihara’s intellectual legacy lies in his capacity to navigate the shifting landscapes of research, adapting seamlessly from cryptography to artificial intelligence and quantum systems. moving forward, his work is expected to contribute significantly to the convergence of computational theory and applied technologies, especially in areas like quantum-enhanced transport and scalable image recognition systems. by combining deep mathematical insight with Image Recognition cutting-edge technologies, ihara is poised to shape the future of secure and intelligent systems across industries.

Notable Publication

Multi-race age estimation based on the combination of multiple classifiers

Conclusion

Yasuyuki Ihara exemplifies a forward-thinking researcher whose foundation in mathematics supports impactful contributions in emerging technologies. his ability to adapt and innovate across domains—especially in areas like quantum computing, computer vision algorithms, AI-driven pattern analysis and power electronics—positions him as a valuable contributor to both academic and industrial advancements. his future work is expected to bridge theoretical innovation with practical applications that shape smarter, more secure digital infrastructures.