Prof. Daniela BURUIANA | Computer Science | Best Researcher Award

Prof. Daniela BURUIANA | Computer Science | Best Researcher Award

Vice-rector, Dunarea de Jos University of Galati, Romania

Prof. Dr. Buruiana Daniela Laura is a prominent academic leader and innovative researcher currently serving as the Vice-Rector at Dunarea de Jos University of Galati . With over two decades of experience in industrial and materials engineering, she holds two habilitations—one in Industrial Engineering and another in Materials Engineering. She leads multiple interdisciplinary initiatives and is the Head of the Department of Materials and Environmental Engineering and the Interdisciplinary Research Centre in Eco-Nano Technology and Advanced Materials (CC-ITI). Her prolific contributions include over 40 ISI-indexed publications, six patents, and leadership in 18 national and international research projects, establishing her as a vital contributor to the advancement of eco-innovative and sustainable technologies 🌱.

Publication Profile

🎓 Education Background

Prof. Buruiana has completed her doctoral studies in Engineering, specializing in the domains of materials and industrial engineering 🏗️. She later earned two habilitations—significant academic milestones that qualify her as a doctoral advisor and research leader in both Industrial Engineering and Materials Engineering. Her academic formation has been deeply rooted in sustainability, biomaterials, and the valorization of industrial and biomedical waste, reflecting her interdisciplinary educational trajectory.

💼 Professional Experience

Currently serving as Vice-Rector, she has held several pivotal academic and research leadership roles, including Head of the Department of Materials and Environmental Engineering since 2020 and Director of CC-ITI. She has directed over 10 competitive research projects, collaborated with global institutions like the University of Burgos (Spain), Universidade de Estado do Rio de Janeiro (Brazil), and The University of Sheffield (UK) 🌍. Her consultancy experience spans five industrial projects, further bridging academia with industry applications. With 14 books published, she also demonstrates a strong commitment to education and scientific communication 📚.

🏅 Awards and Honors

Prof. Buruiana has been honored with 17 awards at conferences and scientific projects, recognizing her innovative research contributions 🏆. She is an active member of the Romanian Society of Biomaterials, the National Register of Teaching Staff Evaluators, and the Romanian Environmental Association. Furthermore, she serves on the Certification Commission for Environmental Study Elaborators and contributes to national education standards through ARACIS. Her professional stature continues to rise due to her impactful research and dedication to excellence.

🔍 Research Focus

Her main research areas include materials engineering, environmental protection, biomaterials, circular economy, and the valorization of waste 🌐. She has significantly contributed to the understanding of eco-friendly nanomaterials and corrosion resistance in harsh environments, while also exploring biomaterial applications for sustainability and CO₂ sequestration. Under her guidance, many young researchers are being trained to implement advanced materials and environmental solutions at an industrial level 🧪.

🧾 Conclusion

Prof. Dr. Daniela Laura Buruiana is a distinguished scholar whose groundbreaking research in industrial and environmental engineering continues to influence scientific innovation and sustainable development worldwide 🌟. Her dynamic leadership, dedication to education, and international collaborations make her a deserving candidate for the Best Researcher Award 🥇.

📚 Top Notable Publications

Evaluating the Impact of Artificial Saliva Formulations on Stainless Steel Integrity (2025) – Applied Sciences
📈 Cited by: 2 articles (Crossref)

Assessment of the Effectiveness of Protective Coatings in Preventing Steel Corrosion in the Marine Environment (2025) – Polymers
📈 Cited by: 3 articles (Crossref)

Advanced Recycling of Modified EDPM Rubber in Bituminous Asphalt Paving (2024) – Buildings
📈 Cited by: 4 articles (Web of Science)

Corrosion Tendency of S235 Steel in 3.5% NaCl Solution and Drinking Water During Six Months of Exposure (2024) – Materials
📈 Cited by: 1 article (Crossref)

Detection of Reed Using CNN Method and Analysis of the Dry Reed (Phragmites Australis) for a Sustainable Lake Area (2023) – Plant Methods
📈 Cited by: 6 articles (Scopus)

Mr. hang du | Programming | Internet of Things Award

Mr. hang du | Programming | Internet of Things Award

student, Nanjing Forestry University, China

Du Hang , a passionate researcher and aspiring innovator in the field of electronic information and FPGA-based hardware acceleration, is currently pursuing his Master’s degree at Nanjing Forestry University. Born in January 2000 in Nanyang, Henan Province, Du Hang has developed a strong academic and technical foundation in electrical engineering and embedded systems. As a member of the Communist Party of China, he is committed to academic excellence and practical innovation in electronic information systems. With a focus on hardware-software co-design, Du actively contributes to high-performance computing projects and has already published scholarly work in international journals.

Publication Profile

Scopus

🎓Education Background:

Du Hang is presently enrolled in the Master’s program in Electronic Information at Nanjing Forestry University (2022.09–2025.06). His coursework includes FPGA technology and application, C/C++ programming, embedded system design, and integrated circuit principles. He completed his undergraduate degree in Electrical Engineering and Automation at Henan University of Science and Technology (2018.09–2022.06), where he gained foundational knowledge in digital electronic technology, power systems, analog circuits, and motor control.

💼Professional Experience:

Du Hang has rich project experience involving advanced hardware design and system-level integration. His work includes the automatic focusing design of a thermal infrared camera using FPGA, FPGA-based machine vision defect detection systems, and the YOLOv4-tiny accelerator design using HLS for real-time object detection. He also led the development of a PC-based temperature and humidity data display system using STM32 and Visual Studio, and implemented a handwritten digit recognition system using PYNQ and LeNet. These projects highlight his strong command over Vivado, HLS, Vitis, and embedded systems, as well as his proficiency in hardware debugging using oscilloscopes and soldering tools.

🏆Awards and Honors:

Du Hang was awarded Second Prize in the 7th JiChuang Competition (East China Division) for his FPGA-based machine vision defect detection system. He holds two patents—one on a hardware acceleration system for target detection and another on a convolutional neural network acceleration architecture based on FPGA. His achievements demonstrate not only technical capability but also innovation under resource-constrained environments.

🔬Research Focus:

Du Hang’s research centers on FPGA-accelerated deep learning, hardware-software co-design, real-time signal processing, and embedded system optimization. He focuses on designing lightweight and high-speed neural network accelerators with techniques such as loop unrolling, channel parallelism, and double-buffer pipelining to enhance throughput and computational efficiency. His work contributes to applications in industrial automation, smart vision, and intelligent embedded systems.

🔚Conclusion:

Du Hang is a dynamic and highly motivated young engineer and researcher whose expertise lies in bridging the gap between algorithm design and hardware implementation. His ability to manage interdisciplinary projects, from coding to PCB-level execution, places him on a promising trajectory in the fields of electronic information and embedded AI systems. With a blend of academic excellence, innovation, and practical skills, Du Hang is poised to make significant contributions to future advancements in intelligent hardware systems.

📚 Top Publication Notes

FPGA Accelerated Deep Learning for Industrial and Engineering Applications: Optimal Design Under Resource Constraints
 Journal: Electronics (Switzerland), 2025
 Published Year: 2025
 Authors: Liu Yanyi, Du Hang, Wu Yin, Mo Tianli
 Cited by: 1 article

Chrysoula Florou | computer programming | Best Researcher Award

Ms. Chrysoula Florou | computer programming | Best Researcher Award

PHD Doctor, University of Thessaly, Greece

👩‍💻 Chrysoula Florou is a dedicated researcher and educator specializing in the intersection of education and programming concepts. With a strong background in computer engineering and a passion for enhancing primary education through innovative tools, she has made significant contributions to improving self-assessment practices for young learners. Beyond academia, she serves as an Officer in the Hellenic Coast Guard, showcasing her versatile professional capabilities.

Publication Profile

Scopus

Education

🎓 Chrysoula’s academic journey reflects her commitment to excellence, earning a Ph.D. (2010–2025) in Electrical and Computer Engineering from the University of Thessaly with a thesis on self-assessment in programming education (“Excellent”). She holds two master’s degrees: one in Informatics focusing on Security and Big Data (2016–2018, “Excellent”) and another in Computer Science and Technology (2009–2011, “Excellent”). Additionally, she completed a diploma in Computer Engineering (2004–2009, “Very Good”) and a certified program in E-Learning Training (2012).

Experience

🧑‍🏫 Chrysoula has extensive teaching experience in programming, database applications, and multimedia at institutions like the University of Thessaly, TEI of Lamia, and DIEK Volos. In parallel, she contributed to European research projects like “cMinds” and worked in IT roles for the Ministry of Health and National Bank of Greece. Since 2011, she has served as an Officer in the Hellenic Coast Guard, balancing her technical expertise with public service.

Awards and Honors

🏆 Chrysoula has earned numerous accolades for her academic excellence, including distinctions for her master’s theses and diploma projects. Her research outcomes have been recognized by leading journals and conferences in the education and programming domains.

Research Focus

🔬 Chrysoula’s research centers on the integration of educational technologies in programming pedagogy, particularly for primary education. She explores self-assessment tools, enhancing teacher facilitation roles, and leveraging innovative software like Scratch for fostering computational thinking in young learners.

Conclusion

🌟 Chrysoula Florou exemplifies the harmony between academia, research, and public service. Her impactful work in education technology and programming continues to inspire both educators and students, shaping the future of learning in primary education.

Publications

The Role of Educators in Facilitating Students’ Self-Assessment in Learning Computer Programming Concepts: Addressing Students’ Challenges and Enhancing Learning.  Journal of Education and Information Technologies, Springer Nature Educ. DOI: 10.1007/s10639-024-13172-2

An autodidactic programming curriculum application for early education: Pilot studies and improvement suggestions.  Proceedings of the 40th SEFI Annual Conference 2012 – Engineering Education 2020: Meet the Future.

3rd graders’ experience on using an autodidactic programming software: A phenomenological perspective. Conference Paper.

 

 

GAN XU | Computer Science | Best Researcher Award

Mr. GAN XU | Computer Science | Best Researcher Award

PhD. candidate, capital university of economics and business, China

Xu Gan is a Doctoral student at Capital University of Economics and Business, Beijing, specializing in Rural Finance, Financial Theory and Policy, and Supply Chain Finance. With a solid academic background and practical experience, Xu has contributed significantly to research in financial services and blockchain technology. 🏛️📚

Profile

Scopus

 

Education

Xu Gan completed a Master of Finance from Capital University of Economics and Business in Beijing (2018-2021) and a Bachelor of Biotechnology from Beijing Union University (2006-2010). Xu also has an extensive academic background in these fields, providing a strong foundation for research and analysis. 🎓📈

Experience

Xu has actively participated in several high-profile research projects, including the National Social Science Foundation of China’s research on rural financial services and the China Mobile Communication Federation’s blockchain technology applications in finance. Xu was responsible for designing research sub-topics and writing research reports. 📊🔬

Research Interests

Xu Gan’s research interests include Rural Finance, Financial Theory and Policy, and Supply Chain Finance. Xu is focused on improving rural financial services and exploring innovative financial technologies such as blockchain. 🌾💡

Awards

Xu has been recognized for academic excellence with several honors: Beijing Outstanding Graduates (2020), Outstanding Graduate of Beijing Union University (2020), and several awards for excellent papers at various financial and rural finance forums. 🏅📜

Publications

Yang, GZ., Xu, G., Zhang, Y., et al. Financial density of village banks and income growth of rural residents. Economic Issues, 2021, 504(08): 89-94.

Zhang, F., Xu, G., Zhang, XY, Cheng, X. Knowledge mapping analysis of seven decades of rural finance research in China. Rural Finance Research, 2020(01): 10-20.

Zhang, F., Xu, G., Cheng, X. A review of blockchain applications in the financial sector. Technology for Development, 2019, 15(08): 865-871.

Hafiza Sadia Nawaz | Computer Science | Women Researcher Award

Dr. Hafiza Sadia Nawaz | Computer Science | Women Researcher Award

Shenzhen University, China

🎓 Dr. H. Sadia Nawaz is a distinguished researcher and academic in Computer Vision, with a Ph.D. from Ocean University of China. Her work focuses on Temporal Activity Detection using Natural Language. With a background in both teaching and research, she has contributed significantly to the field of computer vision and continues to pursue a career as a postdoctoral researcher. Her extensive knowledge and dedication to the subject make her a valuable asset to any research group.

Profile

Scopus

 

Education

📚 Dr. H. Sadia Nawaz holds a Ph.D. in Computer Science from Ocean University of China, specializing in Temporal Moment Localization using Natural Language. She also completed her Master’s in Information Science and Technology at the University of Sargodha and an MS in Computer Science and Technology with a focus on Cyber Security at the University of Lahore. Her academic background provides a strong foundation for her research and teaching roles.

Experience

💼 Dr. Nawaz has a robust teaching background, having served as a Programming Teaching Assistant at Heriot-Watt University and Ocean University of China, and as a Computer Science Lecturer at Superior University of Lahore and the University of Sargodha. Her roles in academia have honed her skills in teaching, mentoring, and research, contributing to her expertise in computer vision and machine learning.

Research Interests

🔍 Dr. Nawaz’s research interests include Activity Localization in Videos via Language, Temporal Moment Detection, and Natural Language Processing. She is particularly focused on moment detection in complex scenarios and the integration of machine learning methods with computer vision techniques to enhance video understanding and activity localization.

Awards

🏅 Dr. H. Sadia Nawaz has been recognized for her research contributions in the field of computer vision, particularly for her work on Temporal Moment Localization using Natural Language. Her research has been published in high-impact journals, reflecting her expertise and commitment to advancing the field.

Publications

Temporal Moment Localization via Natural Language by Utilizing Video Question Answers as a Special Variant and Bypassing NLP for Corpora

IVTEN – Integration of Visual-Textual Entities for Temporal Activity Localization via Language in Video

Revelation of Novel Paradigm in Temporal Moment Localization by Using Natural Language in Video

Multi-level Edges and Context Arranger Architecture Using Referencing Expressions for Temporal Moment Localization via Natural Language

A Frame-Based Feature Model for Violence Detection from Surveillance Cameras Using ConvLSTM Network