Xiaole Han | Blockchain | Best Researcher Award

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Mr. Xiaole Han | Blockchain | Best Researcher Award

Mr. Xiaole Han | Blockchain – PHD student at SEGi University, Malaysia

Han Xiaole is a dedicated researcher and innovator in the field of blockchain technology and its application in supply chain management. With a solid background in engineering and a research-driven mindset, Han has been instrumental in advancing the practical implementation of blockchain systems to improve operational efficiencies across industries. His work bridges technical engineering with management science, reflecting a unique interdisciplinary strength that sets him apart. Han combines his hands-on experience in blockchain R&D with academic rigor, aiming to promote sustainable technological adoption and policy development in emerging economies.

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ORCID | Google Scholar

Education

Han is currently pursuing a Ph.D. in Management Science at SEGi University, where his academic journey is focused on the study of blockchain adoption within supply chain management, particularly for small and medium-sized enterprises (SMEs). His thesis, titled “Blockchain Adoption in Supply Chain Management: Multi-Level Determinants and Policy Implications”, explores the intersection of technology, organizational behavior, and policy. Under the supervision of Dr. Gooi Leong Mow, Han has employed sophisticated methodologies such as Partial Least Squares Structural Equation Modeling (PLS-SEM) and multi-level modeling to investigate the barriers and enablers of blockchain adoption from individual, organizational, and societal perspectives.

Experience

From 2018 to 2020, Han worked as a Blockchain R&D Engineer at the HPB Foundation, where he led several core initiatives. He played a key role in the development of High-Performance Blockchain (HPB) hardware, specifically the BOE acceleration engine, which significantly improved transaction throughput, achieving over 5,000 transactions per second with latency below 100 milliseconds. Additionally, he designed a dual-layer consensus mechanism that balanced decentralization with performance, and created smart contract protocols to enhance data traceability and integrity within supply chains. His technical contributions not only improved blockchain performance but also aligned with real-world industry needs, making his work highly impactful in the enterprise context.

Research Interest

Han’s research interests lie at the intersection of blockchain technology, supply chain management, and innovation policy. He is particularly interested in how blockchain can be sustainably adopted across different levels of an organization and society, including technological readiness, organizational capability, user perception, and regulatory frameworks. His research investigates how SMEs can overcome barriers to adopting emerging technologies and leverage blockchain to gain competitive advantage through enhanced transparency, traceability, and trust. Han’s academic work contributes to filling critical gaps in technology adoption models by integrating multi-level analytical frameworks with blockchain-specific trust and governance mechanisms.

Award

Han Xiaole has been nominated for the [Award Name Placeholder] based on his contributions to blockchain research and innovation. His work exemplifies a blend of theoretical depth and practical application, making a significant contribution to the advancement of supply chain resilience through technology. This nomination reflects his exceptional research impact, technological creativity, and potential for future leadership in the field of management science and digital innovation.

Publications 📚

“Multi-Level Determinants of Sustainable Blockchain Adoption in SCM” – Sustainability, 2025. 🌱🔗DOI: 10.3390/su17062621 | Cited by 23 articles (Google Scholar, 2025) | Integrates individual, organizational, and societal frameworks with blockchain trust models to explain adoption patterns.

Conclusion

Han Xiaole’s career reflects a powerful synergy between advanced research and real-world application. His contributions to blockchain technology, particularly in the context of supply chain management, demonstrate both visionary thinking and technical acumen. Through rigorous academic inquiry and practical innovation, he has helped shape the conversation around sustainable and scalable blockchain adoption. With a strong publication record, technical expertise, and a deep understanding of industry dynamics, Han continues to make a lasting impact in the fields of digital transformation and management science. His work not only advances academic theory but also provides actionable insights for businesses and policymakers navigating the digital economy.

 

Larbi Boubchir | Deep Anomaly Detection in Blockchain | Best Scholar Award

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Prof. Larbi Boubchir | Deep Anomaly Detection in Blockchain | Best Scholar Award 

Professor | University of Paris 8 | France

Based on the detailed profile of Prof. Dr. Larbi Boubchir, here is an analysis of his suitability for the Research for Best Scholar Award, focusing on his strengths, areas for improvement, and a concluding assessment.

Strengths

  1. Extensive Research Contributions: Prof. Boubchir has authored and co-authored over 100 publications, which highlights his prolific output and active engagement in research. His work spans a broad range of topics including artificial intelligence, biometrics, biomedical signal processing, and image processing, demonstrating significant expertise across multiple domains.
  2. Leadership and Organizational Roles: He holds several prominent positions, such as Full Professor, Deputy Director of LIASD, and Head of multiple Master’s programs. His roles in organizing and chairing international workshops and conferences further illustrate his leadership and influence in the academic community.
  3. Recognition and Awards: His achievements include being recognized as an Outstanding Associate Editor by IEEE Access, receiving Best Paper and Best Poster awards, and contributing to notable international research projects. These accolades reflect the high quality and impact of his research.
  4. Diverse Teaching Experience: Prof. Boubchir has a robust teaching background, covering various levels and subjects in computer science, signal and image processing, and artificial intelligence. His pedagogical responsibilities and contributions to curriculum development at several institutions underscore his commitment to education.
  5. Multidisciplinary Research: His work in areas like biometric recognition, biomedical signal processing, and artificial intelligence for cybersecurity highlights his interdisciplinary approach and innovative contributions to multiple fields.

Areas for Improvement

  1. Interdisciplinary Collaboration: While Prof. Boubchir’s research is broad, further collaboration with researchers from different disciplines could enhance the application and impact of his work. For example, integrating perspectives from cognitive sciences or behavioral studies might enrich his research in biometrics and artificial intelligence.
  2. Involvement in Emerging Technologies: Although his research is cutting-edge, staying abreast of emerging technologies such as quantum computing or new AI paradigms could provide additional opportunities for groundbreaking research and keep his work at the forefront of technological advancements.
  3. Increased Focus on Applied Research: While his theoretical and methodological contributions are significant, emphasizing applied research that directly addresses real-world problems and demonstrates practical outcomes could enhance the societal impact of his work.

Short Biography

Prof. Dr. Larbi Boubchir is a distinguished Full Professor of Computer Science at the University of Paris 8, France. With a notable career spanning several institutions, including CNRS and Northumbria University, he has made significant contributions to the fields of artificial intelligence, biometrics, and biomedical signal processing. His role as Deputy Director of the LIASD laboratory and Head of multiple Master’s programs underscores his leadership and influence in both research and education. Prof. Boubchir’s extensive experience in organizing international workshops and conferences further highlights his active engagement with the global academic community.

Profile

ORCID

Education

Prof. Boubchir earned his PhD in Signal and Image Processing from the University of Caen-Basse Normandie in 2007, following a Master of Advanced Studies in Computer Science from Polytech’Tours, University of François-Rabelais, Tours, in 2002. In 2019, he completed his Habilitation à Diriger des Recherches (HDR) at the University of Paris 8, which qualifies him to supervise doctoral research in Computer Science.

Experience

Prof. Boubchir has held numerous academic positions throughout his career. He has been a Full Professor at the University of Paris 8 since 2021, where he also serves as Deputy Director of the LIASD research lab and heads several Master’s programs. Prior to this, he was an Associate Professor at the same institution and held research fellowships at Northumbria University, CNRS, and Qatar University. His diverse teaching experience spans institutions in France, the UK, and Qatar, and includes a range of subjects from computer programming to artificial intelligence.

Research Interests

Prof. Boubchir’s research interests encompass biometrics, artificial intelligence, biomedical signal processing, and image processing. His work involves developing algorithms for biometric recognition, feature engineering, and deep learning applications in biomedical data analysis. He is particularly focused on applications such as biometric authentication, epilepsy detection, and brain-computer interfaces. His interdisciplinary approach combines advanced machine learning techniques with practical applications in security and healthcare.

Awards

Prof. Boubchir has received several prestigious awards, including IEEE Access Outstanding Associate Editor honors (2020, 2021, 2023) and the Best Paper award at the 39th International Conference on Telecommunications and Signal Processing (2016). He also won the Best Poster Award at the 9th International Conference on Software Defined Systems (2022) and achieved recognition for his top papers at IEEE conferences.

Publications

Here are some of Prof. Boubchir’s notable publications:

A Review on Deep Anomaly Detection in Blockchain (2024), Blockchain: Research and Applications.

Enhancing 2D-3D Facial Recognition Accuracy of Truncated-Hidden Faces Using Fused Multi-Model Biometric Deep Features (2024), Multimedia Tools and Applications.

Deep Speech Recognition System Based on AutoEncoder-GAN for Biometric Access Control (2023), International Journal of Advanced Computer Science and Applications (IJACSA).

Efficient Multiplier-Less Parametric Integer Approximate Transform Based on 16-Points DCT for Image Compression (2022), Multimedia Tools and Applications.

Lossy Image Compression Based on Efficient Multiplier-Less 8-Points DCT (2022), Multimedia Systems.

EEG Signal Feature Extraction and Classification for Epilepsy Detection (2022), Informatica.

Detecting African Hoofed Animals in Aerial Imagery Using Convolutional Neural Network (2021), IAES International Journal of Robotics and Automation.

Palm Vein Recognition Based on Competitive Coding Scheme Using Multi-Scale Local Binary Pattern with Ant Colony Optimization (2020), Pattern Recognition Letters.

A Novel and Efficient 8-Point DCT Approximation for Image Compression (2020), Multimedia Tools and Applications.

EEG Epileptic Seizure Detection and Classification Based on Dual-Tree Complex Wavelet Transform and Machine Learning Algorithms (2020), Journal of Biomedical Research.

Conclusion

Prof. Dr. Larbi Boubchir is highly suitable for the Research for Best Scholar Award. His impressive research portfolio, leadership roles, teaching contributions, and recognition from the academic community illustrate his exceptional qualifications. His diverse expertise and significant impact in fields such as artificial intelligence, biometrics, and biomedical signal processing make him a strong candidate for this award. To further strengthen his profile, focusing on interdisciplinary collaborations, emerging technologies, and applied research could provide additional avenues for innovation and impact. Overall, Prof. Boubchir’s accomplishments and contributions make him a distinguished candidate deserving of recognition.

Veneta Aleksieva | Blockchains | Best Researcher Award

Posted on by Academic achievements

Prof. Dr. Veneta Aleksieva | Blockchains | Best Researcher Award

Veneta Aleksieva | Technical University of Varna | Bulgaria

Based on Veneta Panayotova Aleksieva’s background and achievements, here is an assessment for the Research for Best Researcher Award, focusing on strengths, areas for improvement, and a conclusion:

Strengths for the Award

  1. Extensive Experience and Expertise:
    • Academic and Professional Background: Aleksieva has a robust academic background with multiple degrees in Computer Science, Electrical Engineering, and Economics. Her extensive work experience spans from early programming roles to current professorship, showcasing a deep and broad understanding of her field.
    • Teaching and Curriculum Development: As a Professor and Instructor at the Technical University of Varna, she has demonstrated significant expertise in areas such as computer networks, network administration, and programming. Her role as Head of the Department of Computer Science and Engineering further highlights her leadership and influence in academia.
  2. Certification and Specialized Skills:
    • Networking and Design Certifications: Aleksieva holds prestigious certifications, including Cisco Certified Network Associate (CCNA) and Cisco Certified Academy Instructor (CCAI). These certifications underscore her technical proficiency and her ability to train others in networking, which is a valuable asset in the field of computer science.
    • Design and Analysis Skills: Her certification as an R&M freenet Certified Designer and her experience in designing electrical blueprints add to her credibility and technical skill set, particularly in the context of network design and infrastructure.
  3. Publication Record:
    • Research Contributions: Aleksieva has authored several publications in areas related to e-learning, network performance analysis, and educational technology. Her research, particularly on the quality of e-learning and network performance, indicates a focus on relevant and impactful topics in her field.
  4. Communication and Organizational Skills:
    • Effective Communication: Her communication skills, honed through teaching and research, are crucial for both academic collaboration and student engagement. Her ability to present complex technical concepts clearly adds value to her research and teaching efforts.

Areas for Improvement

  1. Broader Research Impact:
    • Increased Publication and Citations: While Aleksieva has a commendable list of publications, increasing the number of publications in high-impact journals and enhancing citation rates could further elevate her research profile. Collaborations with international researchers and participation in global conferences could help achieve this.
  2. Research Diversification:
    • Exploring New Research Areas: Aleksieva could consider expanding her research to include emerging areas in computer science and technology, such as artificial intelligence, machine learning, or cybersecurity. This diversification could enhance the relevance and applicability of her research in the rapidly evolving tech landscape.
  3. Funding and Grants:
    • Securing Research Grants: Pursuing research grants and funding opportunities could support larger-scale projects and collaborative research efforts. Engaging with funding bodies and exploring research partnerships could provide additional resources for innovative research.

Short Biography

Veneta Panayotova Aleksieva is a distinguished professor at the Technical University of Varna, Bulgaria, specializing in computer science and engineering. With a career spanning over two decades, she has made significant contributions to the fields of computer networks, network administration, and e-learning. As the Head of the Department of Computer Science and Engineering, she leads the development of cutting-edge curricula and fosters advancements in network technologies and educational methodologies. Her dual expertise in both theoretical and practical aspects of computing makes her a highly respected figure in her academic community.

Profile

ORCID

Education

Veneta Aleksieva’s educational background is robust and diverse. She earned her PhD in Computer Science from the Technical University of Varna (2008-2012), following an M.S. degree in Electrical Engineering in Industry from the same institution (2008-2010). Her academic journey also includes an M.S. degree in Economics (accounting and control) from the University of Economics – Varna (1999-2000) and a Bachelor’s degree in Economics (accounting and control) from the same university (1994-1999). Additionally, she completed industrial design training at the Technical University of Varna (1992-1993) and holds a degree in Computer Science from the same institution (1988-1993).

Experience

Veneta Aleksieva’s professional experience is extensive and varied. Since 2006, she has served as a Professor and Instructor at the Technical University of Varna, where she has taught computer networks, network administration, and programming. She has been instrumental in preparing students for Cisco certifications and has overseen the Department of Computer Science and Engineering as its Head since the end of 2023. Prior to her current role, she worked as a designer at PAN39 Ltd., a teacher of informatics and information technologies, and as a programmer at Emir Ltd. and Ekom Ltd. Her early career included roles in administrative activities and software testing, demonstrating her broad expertise across different aspects of technology and education.

Research Interests

Veneta Aleksieva’s research interests are centered on computer networks, network performance analysis, and e-learning technologies. Her work focuses on improving network infrastructure and performance, developing efficient educational tools, and enhancing the quality of e-learning environments. She is particularly interested in the intersection of technology and education, exploring how digital tools and methodologies can be optimized to improve learning outcomes and network reliability.

Awards

Veneta Aleksieva has received recognition for her contributions to the fields of computer science and education. Her certifications as a Cisco Certified Network Associate (CCNA) and Cisco Certified Academy Instructor (CCAI) are notable achievements, reflecting her expertise and commitment to advancing networking education. Additionally, her work as an R&M freenet Certified Designer highlights her proficiency in network design and infrastructure.

Publications

Aleksieva, V., & Nenov, H. (2005). “Quality of Feedback Based on Electronic Tests in E-Learning Training.” Computer Science and Technology, 2, 81-87. Link

Nenov, H., & Aleksieva, V. (2006). “Quality of Feedback in E-Learning Training.” In: Proceedings of the Second National Conference on E-Learning in Higher Education, 129-132. ISBN 954-07-2413-9.

Nenov, H., & Aleksieva, V. (2006). “Evaluation Based on Electronic Tests.” In: Proceedings of the Second National Conference on E-Learning in Higher Education, 129-132. ISBN 954-07-2413-9.

Aleksieva, V. (2007). “The Problems in Distant-Learning.” In: iCEST2007 Proceedings of Papers, 2, 621-622. ISBN 9989-786-06-2.

Aleksieva, V., & Antonov, P. (2008). “A Model for Network Performance Analysis in Case of Transfer of Large Image Files.” In: ICEST2008 Proceedings, Nish, Serbia, 60-67. ISBN 978-86-85195-59-4.

Aleksieva, V., & Gerasimov, K. (2008). “Expansion of AutoCAD Functionality for Minimizing 2D Electrical Blueprints Development Time.” In: ISCCS2008 Proceedings, Kavala, Greece, 356-362. ISBN 978-954-580-254-6.

Aleksieva, V., & Atanasova, D. (2008). “User Interface for Quick Testing of Internet Connectivity.” In: ISCCS2008 Proceedings, Kavala, Greece, 326-331. ISBN 978-954-580-254-6.

Aleksieva, V. (2009). “Study of the ‘E-Learning Quality – Students’ Satisfaction’ Link.” In: Proceedings of the Third National Conference with International Participation on E-Learning in Higher Education, Svishov, 117-125. ISBN 978-954-23-0427-2.

Aleksieva, V. (2009). “Relationship between E-Learning Quality and Feedback about Students’ Satisfaction.” In: ICEST2009 Proceedings, Veliko Tarnovo, Bulgaria, 473-477.

Aleksieva, V. (2009). “Multisensory and Multimodal Online Learning.” In: Conference on Quality of Higher Education in Bulgaria – Problems and Perspectives 2009, Rousse, 45-51. ISSN 1314-0051.

Conclusion

Veneta Panayotova Aleksieva is a strong candidate for the Research for Best Researcher Award. Her extensive academic background, certifications, and contributions to research and teaching make her a notable figure in her field. While there are opportunities for improvement, such as increasing publication impact and diversifying research topics, her current strengths and achievements position her as a valuable contributor to the field of computer science and engineering. Her dedication to advancing knowledge through both teaching and research underscores her suitability for the award.