Prof. Daniela BURUIANA | Computer Science | Best Researcher Award

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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)

Zhizhen Chen | Computer Science | Best Researcher Award

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Dr. Zhizhen Chen | Computer Science | Best Researcher Award

Senior Lecturer, University of Greenwich, United Kingdom

🎓 Dr. Zhizhen Chen is a dedicated academic professional serving as a Senior Lecturer in Finance at the University of Greenwich since 2017. With a rich background in finance and economics, Dr. Chen brings extensive experience from both academia and industry. His research interests encompass financial markets, risk management, and financial engineering, contributing significantly to several top-tier finance journals. Dr. Chen is also an active peer reviewer and passionate educator, sharing his expertise through innovative courses like Fintech Banking and Financial Engineering and Machine Learning. 🌍📊

Publication Profile

Scopus

Strengths for the Award:

  1. Research Excellence: Dr. Chen has a strong publication record, with multiple articles published in high-impact journals such as “Journal of International Money and Finance” and “Research in International Business and Finance,” both rated 4* in SJR. This demonstrates his capability in producing high-quality research in the field of finance.
  2. Peer Review Activities: He has been a peer reviewer for several prestigious journals since 2016, which showcases his recognition in the academic community and his commitment to advancing knowledge in finance.
  3. Academic and Professional Credentials: Dr. Chen holds a PhD in Finance, is a Fellow of the Higher Education Academy, and has passed CFA Level 1. This combination of academic qualifications and professional certification adds to his credibility and expertise in the field.
  4. Diverse Teaching Portfolio: His teaching experience spans various finance and economics-related courses, demonstrating versatility and a solid understanding of different areas within the field.
  5. Industry Experience: Dr. Chen’s experience as an Investment Analyst and his work with financial institutions provide him with practical insights, enhancing his academic work’s relevance and applicability.
  6. Continuous Professional Development: His commitment to continuous learning and development is evident through his successful completion of the CFA Level 1 exam and his role in ongoing staff development activities.

Areas for Improvement:

  1. Broader Research Impact: While Dr. Chen has a strong record in finance-specific publications, expanding his research impact across other interdisciplinary areas, such as sustainable finance or fintech, could further enhance his profile.
  2. Leadership Roles in Research: Taking on more leadership roles in research projects or academic committees could strengthen his candidacy by demonstrating his influence beyond his individual contributions.
  3. Grants and Funding: Securing research grants or funding is a notable achievement in academia that is not highlighted in the current profile. Pursuing funding opportunities could bolster his research credentials further.

Education

🎓 Dr. Zhizhen Chen holds a PhD in Finance from the University of Glasgow (2018), demonstrating his strong foundation in financial research and education. He is also a Fellow of the Higher Education Academy (2017), a testament to his commitment to teaching excellence, and he earned an MSc in Economics from the University of Wuhan (2012). 📚✨

Experience

🌟 Dr. Chen’s career spans roles as a Senior Lecturer in Finance at the University of Greenwich since 2017, where he excels in teaching and research. His prior experience includes serving as a Research Assistant and Teaching Assistant at the University of Glasgow, and an Investment Analyst at ICBC Wuhan. This blend of academic and industry roles has equipped him with a unique perspective on finance education. 💼💹

Research Focus

🔍 Dr. Chen’s research is focused on financial markets, risk management, securitization, and financial engineering. He actively contributes as a peer reviewer for prestigious journals, including the Journal of International Financial Markets, Institutions & Money, and Finance Research Letters, ensuring rigorous academic standards in the field. 📑🔬

Awards and Honours

🏅 Dr. Chen was recognized as a Fellow of the Higher Education Academy in 2017, highlighting his dedication to teaching excellence. In addition, he passed the CFA Level 1 exam in 2020, demonstrating his commitment to continuous professional development in finance. 🎖️📈

Publication Top Notes

Lin, W., Yan, W., Chen, Z., Xiao, R. (2023). Research on product appearance patent spatial shape recognition for multi-image feature fusion. Multimedia Tools and Applications (SJR 3*).

Xiao, R., Li, G., Chen, Z. (2023). Research progress and prospect of evolutionary many-objective optimization. Control and Decision.

Chen, Z., Liu, H., Peng, J., Zhang, H., Zhou, M. (2022). Securitization and bank efficiency. In: Ferris, S.P., Kose, J., Makhija, A.K., (eds.) Empirical Research in Banking and Corporate Finance. Emerald Publishing Limited.

Conclusion:

Dr. Zhizhen Chen is a suitable candidate for the “Research for Best Researcher Award” due to his significant contributions to the field of finance through high-quality publications, peer-review activities, and professional development. While there is room for growth in interdisciplinary research and leadership roles, his current achievements and ongoing commitment to both academic and professional excellence make him a compelling contender for the award.

Ke Wu | Computer Science | Best Dissertation Award

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Prof. Ke Wu | Computer Science | Best Dissertation Award

professor, China University of Geosciences (Wuhan), China

Dr. Ke Wu is a distinguished professor at the China University of Geosciences, specializing in hyperspectral remote sensing and its applications in geosciences 🌏. Born on October 2, 1981, in Hubei, China, Dr. Wu has established himself as a leading expert in his field, contributing significantly to research and education 📚. Fluent in both Chinese and English, he excels in both written and spoken communication, making him a valuable asset to the academic community.

Profile

ORCID

 

Education

Dr. Ke Wu holds a Ph.D. in Photogrammetry and Remote Sensing from Wuhan University (2008) 🎓, where he also completed his B.S. in Information Engineering (2002) 🏫. His advanced education has provided a strong foundation for his research and teaching career in remote sensing and geophysics.

Experience

Since January 2020, Dr. Ke Wu has been a professor at the China University of Geosciences 👨‍🏫. Prior to this, he served as an associate professor from 2011 to 2019 and as a postdoctoral researcher in geophysics from 2009 to 2011. His extensive experience in academia has enabled him to mentor many students and contribute to numerous research projects.

Research Interests

Dr. Ke Wu’s research interests focus on hyperspectral remote sensed image processing and its applications in geosciences 🔬. He has led several significant research projects funded by the National Natural Science Foundation of China and other prestigious organizations. His work aims to advance the understanding and practical applications of remote sensing technologies.

Awards

In recognition of his contributions to the field, Dr. Ke Wu and his team have received numerous awards 🏆. Notably, in 2022, they won the third prize in the National Hyperspectral Satellite Remote Sensing Image Intelligent Processing and Industry Application Competition of the “Obit Cup”. His group also secured the third prize in the South Division of the “Yuan Chuang Cup” Innovation and Creativity Competition in 2019 and the first prize of the Surveying and Mapping Science and Technology Progress Award of the China Society of Surveying, Mapping, and Geographic Information in 2017.

Publications

Junfei Zhong, Ke Wu, Ying Xu* (2024). “Deep Spatial Feedback Refined Network with Multi-Level Feature Fusion for Hyperspectral Image Sub-pixel Mapping,” IEEE Transactions on Geoscience and Remote Sensing. DOI: 10.1109/TGRS.2024.3419157 – Cited by: 3 articles

Ke Wu, Fan Yang, Huize Liu, Ying Xu* (2024). “Detection of coral reef bleaching by multitemporal Sentinel-2 data using the PU-bagging algorithm: A feasibility study at Lizard Island,” Remote Sens. DOI: 10.3390/rs16132473 – Cited by: 5 articles

Ke Wu, Yanting Zhan, Ying An, Suyi Li* (2024). “Multiscale Feature Search-Based Graph Convolutional Network for Hyperspectral Image Classification,” Remote Sens. DOI: 10.3390/rs16132328 – Cited by: 4 articles

Wenjie Tang, Ke Wu, Yuxiang Zhang, Yanting Zhan* (2023). “A Siamese Network Based on Multiple Attention and Multilayer Transformer for Change Detection,” IEEE Transactions on Geoscience and Remote Sensing. DOI: 10.1109/TGRS.2023.3325220 – Cited by: 6 articles

Yanting Zhan, Ke Wu, Yanni Dong* (2022). “Enhanced Spectral–Spatial Residual Attention Network for Hyperspectral Image Classification,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. DOI: 10.1109/JSTARS.2022.3197934 – Cited by: 8 articles

GAN XU | Computer Science | Best Researcher Award

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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

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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

HaiTian Chen | Computer Science | Best Researcher Award

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Ms. HaiTian Chen | Computer Science | Best Researcher Award

College of Science, North China University of Science and Technology, China

Chen HaiTian is a dedicated researcher in the field of Cyberspace Security from China. Born in December 1998, Chen has made significant strides in federated learning, privacy preservation, and cybersecurity. His contributions span multiple peer-reviewed journals and patents, showcasing his commitment to advancing technology and safeguarding digital spaces.

Profile

ORCID

 

Education

Chen HaiTian holds a major in Cyberspace Security, demonstrating his expertise and focus in this critical area of study. His academic background has equipped him with the skills and knowledge necessary to tackle complex cybersecurity challenges and contribute to innovative solutions in the field. 🎓

Research Interests

Chen HaiTian’s research interests focus on federated learning, privacy preservation, and cybersecurity. He is particularly interested in developing robust aggregation techniques to defend against poisoning attacks in federated learning and exploring personalized fair split learning for resource-constrained Internet of Things (IoT). 🔍

Awards

Chen HaiTian has received recognition for his contributions to software development, including the Huali Academy Backstage Management System V1.0 and the DC Early Warning System V1.0. His work has been registered with computer software registration numbers, showcasing his achievements in developing innovative solutions for network management and security. 🏆

Publications

Chen, H.; Chen, X.; Peng, L. (2023). FLRAM: Robust Aggregation Technique for Defense Against Byzantine Poisoning Attacks in Federated Learning. Electronics. Cited by Electronics.

Chen, H.; Chen, X.; Peng, L. (2024). Personalized Fair Split Learning for Resource-Constrained Internet of Things. Sensors, 24, 88. Cited by Sensors.

Chen, H., Chen, X., Ma R., et al. (2024). A federated learning privacy preserving approach for remote sensing data. Computer Applications. Cited by Computer Applications.

Chen, H., Chen, X. (2023). A Robust Aggregation Technique for Poisoning Attack Defense in Federated Learning. Cited by Journal.

Xu C., Zhang S., Chen H., et al. (2024). A federated learning approach based on adaptive differential privacy and customer selection optimization. Computer Applications. Cited by Computer Applications.

Peng L., Zhang S., Chen H., et al. (2023). Clustered federated learning based on improved CFSFDP algorithm. Journal of North China University of Science and Technology (Natural Science Edition). Cited by NCUST.

Qiang Li | Computer Science | Best Researcher Award

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Mr. Qiang Li | Computer Science | Best Researcher Award

Lecturer, Qingdao University, China

Dr. Li Qiang is an experienced lecturer in computer science with a PhD in Engineering. He specializes in high-performance computing and has a strong background in both teaching and research. Committed to fostering academic excellence and technological innovation, Dr. Li has been a dedicated educator and researcher at Qingdao University since 2015.

Profile

ORCID

 

Education 🎓

PhD in Engineering: University of the Chinese Academy of Sciences, Computer Network Information Center (2010-2014), Advisor: Lu Zhonghua. Master’s in Information Science and Engineering: Shandong University of Science and Technology (2007-2010), Advisor: Zhao Maoxian. Bachelor’s in Education: Qingdao University (2003-2007).

Experience 👨‍🏫

Lecturer at Qingdao University, School of Computer Science and Technology (January 2015-Present). Teaching undergraduate and graduate courses in computer science. Supervising student research projects and theses. Conducting research in high-performance computing. Published 12 research papers in journals and conferences. Granted 2 patents.

Research Interests 🔬

Dr. Li Qiang’s research interests lie in high-performance computing, particularly in the optimization and parallel implementation of numerical simulations and the development of new computational frameworks. His work focuses on enhancing computational efficiency and scalability in large-scale scientific computations.

Awards 🏆

Dr. Li Qiang has been recognized for his contributions to the field of high-performance computing through multiple publications and patents. His innovative work has led to advancements in computational methods and has garnered attention in the academic community.

Publications 📄

Optimization Research of Heterogeneous 2D-Parallel Lattice Boltzmann Method Based on Deep Computing Unit. Appl. Sci. 2024, 14, 6078.

Heterogeneous Parallel Implementation of Large-Scale Numerical Simulation of Saint-Venant Equations. Appl. Sci. 2022, 12, 5671. Cited by 6

The Study of Parallelization of SWAT Hydrology Cycle. The 32nd ACM International Conference on Supercomputing, Beijing, 2018. [Cited by 3]

A New Parallel Framework of Distributed SWAT Calibration. Journal of Arid Land, 2015, 7(1): 122-131. [Cited by 7]

Parallel Simulation of High-Dimensional American Option Pricing Based on CPU VS MIC. Concurrency and Computation: Practice and Experience, 2014, 27(5): 1110-1121. [Cited by 5]

Zhiping Liu | Human-Computer Interaction | Best Researcher Award

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Mr. Zhiping Liu | Human-Computer Interaction | Best Researcher Award

Researcher, Zibo Comprehensive Bonded Zone Development Service Center, China

Zhiping Liu is a dedicated researcher at the Zibo Comprehensive Bonded Zone Development Service Center in Zibo, Shandong Province, China. With a multifaceted background that spans Industrial Design Engineering, Biomedical Engineering, Psychology, and Computer Science, Zhiping brings a rich blend of theoretical knowledge and practical expertise to his work. He focuses on enhancing digital user experiences through innovative interface designs, integrating both aesthetic and functional elements.

Profile

ORCID

Education 🎓

Zhiping Liu holds a Master’s degree in Industrial Design Engineering from the Mechanical College of Shandong University. His academic journey has provided him with a robust foundation in various disciplines, including Industrial Design Engineering, Biomedical Engineering, Psychology, and Computer Science, equipping him with the skills needed to excel in the field of digital interface design.

Experience 🛠️

Zhiping’s professional experience is marked by his involvement in various research and consultancy projects at the Zibo Comprehensive Bonded Zone Development Service Center. He has played a pivotal role in optimizing digital interfaces, leveraging his expertise to improve user satisfaction and interface efficiency. His work often involves the integration of the Analytic Hierarchy Process with visual design elements, aiming to create more intuitive and effective digital solutions.

Research Interests 🔍

Zhiping Liu’s research interests lie in digital interface design, user experience optimization, and the integration of aesthetic and functional aspects in digital products. His innovative approach involves using the Analytic Hierarchy Process to enhance visual design elements, thereby improving the overall efficiency and user satisfaction of digital interfaces. He is keen on exploring new methodologies that bridge the gap between subjective aesthetic judgments and objective usability metrics.

Awards 🏆

Zhiping Liu has made notable contributions to the field of digital interface design, earning recognition for his innovative research methods. His work on integrating the Analytic Hierarchy Process with visual design principles has been particularly impactful, offering a structured approach to optimizing digital interfaces. Through his research, Zhiping has provided valuable insights and advancements that have significantly improved the field’s understanding and application of digital design principles.

Publications 📚

Liu, Z., “Integrating Analytic Hierarchy Process with Visual Design Elements,” International Journal of Human-Computer Interaction, 2023. [Cited by: 12 articles]

Liu, Z., “Optimizing User Experience through Digital Interface Design,” Journal of Digital Design, 2022. [Cited by: 8 articles]

Liu, Z., “Aesthetic and Functional Integration in Digital Products,” Design Science Journal, 2021. [Cited by: 10 articles]