Oussama El Othmani | Computer Science and Artificial Intelligence | Best Innovation Award

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Mr. Oussama El Othmani | Computer Science and Artificial Intelligence | Best Innovation Award

Ecole Polytechnique de Tunisie | Tunisia

Oussama El Othmani is an emerging researcher and software engineer whose work bridges artificial intelligence, explainable machine learning, and applied computer engineering. He is currently pursuing a PhD in ETIC, following a strong academic foundation in computer engineering and preparatory mathematics–physics, with rigorous training in artificial intelligence, advanced learning algorithms, computer architecture, databases, and software methodology. Professionally, he has contributed to complex, mission-critical software systems, working across the full software development lifecycle while applying agile methodologies, object-oriented design, and hardware-aware optimization. His research interests focus on explainable and interpretable AI, machine learning, rough set theory, soft computing, computer vision, natural language processing, and AI applications in healthcare and high-stakes decision systems. He has led and contributed to multiple applied AI projects, including medical chatbots, diagnostic decision-support systems, blood anomaly detection, and antibiotic resistance classification. His scholarly output includes peer-reviewed publications in applied AI, He has also gained recognition through research-driven projects aligned with national and institutional initiatives. Overall, his profile reflects a strong balance of academic research, applied innovation, and real-world impact, positioning him as a promising contributor to the future of trustworthy and explainable artificial intelligence.

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Dapeng Zhang | Engineering and Technology | Research Excellence Award

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Dr. Dapeng Zhang | Engineering and Technology | Research Excellence Award

 Guangdong Ocean University | China

Dr. Dapeng Zhang is an Associate Professor in Ocean Engineering at Guangdong Ocean University, China, with expertise in the dynamic response of offshore and subsea structures. He earned his Doctor of Engineering from Zhejiang University through a joint PhD program with the University of Lisbon, following a Master of Engineering from Ningbo University.  He was recognized among the top 5% of highly cited scholars by CNKI, highlighting his influence in marine and offshore engineering. His research spans marine engineering structures, pipelines and risers, offshore oil underwater production systems, marine artificial intelligence, and triboelectric nanogenerators (TENG). Dr. Zhang has published extensively in leading JCR Q1 journals such as Ocean Engineering, Physics of Fluids, Marine Structures, and Aquacultural Engineering, contributing foundational and applied insights into subsea dynamics, hydrodynamics, and deployment optimization. He serves as Editor-in-Chief of Engineering Solutions to Mechanics, Marine Structures and Infrastructures, holds additional editorial roles, and acts as a reviewer for numerous international journals. Overall, his scholarship integrates theory, computation, and engineering practice to advance safe, efficient, and intelligent offshore systems.

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Dynamic analysis of towed cable with variable length during turning maneuvers

Scientific Reports, 13(1), 3525, 2023 · Citations: 23

Amir Hossein akbari | Engineering and Technology | Research Excellence Award

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Dr. Amir Hossein akbari | Engineering and Technology | Research Excellence Award

Iran University of Science and Technology | Iran

Amir Hosein Akbari is an accomplished researcher in industrial engineering with a strong record of scholarly impact his academic background is grounded in advanced industrial engineering education, complemented by progressive research experience spanning optimization, decision sciences, and intelligent systems. His professional experience includes active involvement in high-quality research collaborations and contributions to applied and theoretical studies addressing complex industrial and societal problems. His core research interests focus on supply chain management, optimization, meta-heuristic and evolutionary algorithms, scheduling, decision support systems, and artificial intelligence–driven industrial applications, with several influential works in expert systems, soft computing, and manufacturing systems. His publications have appeared in high-impact venues such as Expert Systems with Applications, Soft Computing, and Neural Computing and Applications, reflecting both methodological rigor and practical relevance. Recognition of his work is demonstrated through strong citation performance and collaborations with well-established scholars in operations research and industrial engineering. Overall, his research portfolio highlights a consistent commitment to advancing intelligent optimization methods and decision-making frameworks, contributing valuable insights to academia and industry while strengthening the scientific foundations of modern industrial engineering.

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Pan Li | Chemistry and Materials Science | Best Researcher Award

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Dr. Pan Li | Chemistry and Materials Science | Best Researcher Award

Academy of Military Science of the People’s Liberation Army | China

Li Pan is a PhD candidate and active researcher at the Academy of Military Sciences, specializing in computational and experimental materials science. Her academic training and doctoral education are grounded in advanced materials engineering, with a strong emphasis on first-principles calculations and microstructural analysis of alloys. Through her research experiencez, she has developed a solid theoretical and practical understanding of alloy design, phase stability, and structure–property relationships at the atomic and microstructural scales. Li Pan has authored more than 10 peer-reviewed scientific articles published in high-impact journals, including Nature Communications, reflecting the quality and relevance of her work. In addition to journal articles, she has authored one scholarly monograph, highlighting her ability to synthesize complex scientific knowledge into cohesive academic work. Her research interests include density functional theory, alloy microstructure evolution, and computational materials modeling. She has received academic recognition for her research productivity and innovation during her doctoral studies. Overall, Li Pan represents an emerging scholar in materials science whose work contributes to advancing the fundamental understanding and design of advanced alloy systems.

Profile : Orcid

Featured Publications

Pan, L., Huang, L., Wang, X., Xu, W., Zhou, Y., & Chen, J. (2025). Pressure effect on structural, mechanical, electronic and thermodynamic properties of Cr–Co sigma phase using first-principles method. Philosophical Magazine.

Pan, L., Chen, J., Huang, L., & Zhang, J. (2024). First-principles study of structural, mechanical, electronic properties and Debye temperature of NbCo₂ Laves phases under pressure. Physica B: Condensed Matter, —, 415683.

Pan, L., Chen, J., Huang, L., & Zhang, J. (2023). Site occupancy and electronic properties of NbCo₂ Laves phases doped with Re. Computational and Theoretical Chemistry, —, 114389.

Pan, L., Huang, L., Chen, J., & Zhang, J. (2023). Site occupancy of Ru in μ phases: A density functional theory study. International Journal of Modern Physics B, —, 23502648.

Pan, L., Huang, L., Chen, J., & Zhang, J. (2022). First-principles study of Co₂₁W₁₈ with pressure effect: Structural, mechanical, electronic properties and Debye temperature. Materials Today Communications, —, 104276.

Ho-jun Song | Computer Science and Artificial Intelligence | Research Excellence Award

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Mr. Ho-jun Song | Computer Science and Artificial Intelligence | Research Excellence Award

Postech | South Korea

Ho-jun Song is a dedicated researcher and Ph.D. candidate in Computer Science and Engineering, specializing in federated learning, edge intelligence, and AIoT systems. With an academic foundation grounded in advanced distributed learning, he has contributed to developing personalized, scalable, and diffusion-based FL frameworks tailored for heterogeneous and resource-constrained environments. He has gained extensive experience through work on edge AI architectures, large-scale experimental pipelines, and applied AI systems for surveillance, security, and military decision support. Professionally, he leads AI initiatives as the Head of AI Development at the Army Artificial Intelligence Center, overseeing deepfake detection, ontology-based LLM systems, and intelligent multi-sensor surveillance solutions. His research interests span federated learning, personalized models, diffusion-based FL, distributed deep learning, and AIoT innovation. His academic journey includes rigorous research under expert mentorship and collaborations with interdisciplinary teams. Although early in his career, he has already contributed impactful ideas such as multidimensional trajectory optimization for FL personalization. He aspires to advance secure, efficient, and adaptive AI systems while contributing to global AI research communities through innovative, mission-driven research.

Profile : Orcid

Featured Publications

Song, H.-J., & Suh, Y.-J. (2025). HyFLM: A hypernetwork-based federated learning with multidimensional trajectory optimization on diffusion paths. Electronics, 14, Article 4704.

Rafael Rebelo | Chemistry and Materials Science | Best Researcher Award

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Mr. Rafael Rebelo | Chemistry and Materials Science | Best Researcher Award

University of Coimbra | Portugal

Rafael C. Rebelo is a Biomedical Engineer and Chemical Engineering PhD researcher recognized for his contributions to cellulose-based materials and sustainable polymer engineering, with an estimated h-index of 0, more than 1 scientific documents, and over 0 citations across journals, patents, and conference contributions. He holds an Integrated Master’s in Biomedical Engineering and is currently pursuing a PhD focused on developing innovative cellulose-based hydrogels for agriculture and environmental applications. Rafael has gained extensive research experience as a Research Fellow in multiple industry-linked projects, contributing to biodegradable polymers, sustainable packaging, polymer degradation, and advanced cellulose composites. His work spans controlled polymerization, hydrogel engineering, green materials processing, and biocompatible systems for healthcare, including efforts in 3D printing and personal care technologies. He has co-authored several high-impact publications and contributed to an international patent on poly(lactic acid)–polyester formulations. Rafael has participated in numerous international conferences through oral presentations and posters, reflecting his active engagement in scientific dissemination. His research interests lie in cellulose chemistry, biodegradable materials, environmental technology, polymer composites, and bio-based engineering solutions. Committed to sustainability and innovation, Rafael aims to advance eco-friendly materials for agriculture, healthcare, and industrial applications, fostering global collaboration and impactful scientific progress.

Profile : Scopus

Featured Publications

Rebelo, R. C., Fonseca, A. C., Coelho, J. F. J., et al. (2025). A sustainable synthesis of cellulose hydrogels for agriculture with repurpose of solvent as fertilizer. Carbohydrate Polymers, 368, 124156.

Silva, R., Medeiros, M., Paula, C. T. B., et al. (2025). Light-mediated 3D-printed wound dressings based on natural polymers with improved adhesion and antioxidant properties. Polymers, 17(8), 1114.

Simões, B., Rebelo, R. C., Ledesma, S., et al. (2025). Development of polyampholyte cellulose-based hydrogels for diapers with improved biocompatibility. Gels, 11, 282.

Silva, R., Rebelo, R. C., Paula, C. T. B., et al. (2025). All-cellulose resin for 3D printing hydrogels via digital light processing (DLP). International Journal of Biological Macromolecules, 306, 141389.

Moreira, R., Pereira, V. A., Rebelo, R. C., et al. (2025). A new and easy-to-implement green packaging option with recycled paperboard and PBAT film. Polymer, 311, 127480.

mozhgan sepahvandian | Chemistry and Materials Science | Editorial Board Member

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Dr. mozhgan sepahvandian | Chemistry and Materials Science | Editorial Board Member

Lorestan University | Iran

Dr. Mozhgan Sepahvandian is an accomplished inorganic chemist with extensive expertise in designing and synthesizing novel inorganic compounds with applications in catalysis, materials science, and environmental chemistry. She earned her Ph.D. in Inorganic Chemistry and has since contributed significantly to both academic research and collaborative industrial projects. With an h-index of [0], over [3] publications, and [0] citations, her work is widely recognized in the scientific community. She has completed and currently leads 10 innovative research projects and has published in reputable journals including SCI and Scopus-indexed outlets. Her research interests span advanced synthesis techniques, coordination chemistry, and sustainable inorganic materials. Dr. Sepahvandian has participated in consultancy and collaborative initiatives bridging academic research with practical industrial applications. Her contributions have been acknowledged through multiple awards and honors, reflecting her dedication to scientific excellence. Beyond research, she actively engages in editorial duties and professional memberships, fostering scientific discourse and mentorship. Her work continues to advance the field of inorganic chemistry, providing impactful solutions for modern technological and environmental challenges. Dr. Sepahvandian’s dedication to innovation, research excellence, and knowledge dissemination marks her as a distinguished scientist and a role model in her field.

Profile : Scopus

Featured Publications

Sepahvandian, M., Coauthor, A., & Coauthor, B. (2025). Exploring limonene adsorption on magnesium and selenium doped AlP nanosheets: A DFT study. Computational Condensed Matter.

Liu Ying | Mechanical Engineering | Research Excellence Award

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Dr. Liu Ying | Mechanical Engineering | Research Excellence Award

East China Jiaotong University | China

Ying Liu is a dedicated researcher and Lecturer specializing in vehicle engineering with a strong academic trajectory and growing research impact, reflected in an h-index of 2, 4 published documents, and 14 citations across indexed platforms. She earned a combined Master’s and PhD degree in Mechanical Engineering from Shanghai University, followed by a Bachelor’s degree in Mechanical Design, Manufacturing and Automation from Changchun Institute of Technology. Her professional career includes serving as a Lecturer at East China Jiaotong University, where she contributes to teaching, mentoring, and interdisciplinary research. Her work focuses on target optimization, image detection, reinforcement learning, computer vision, intelligent control, and smart vehicle technologies. She has completed five research projects, contributed to two national-level and multiple provincial and horizontal projects, and actively engages in consultancy with ten industry-linked initiatives. She has authored seven SCI-indexed papers, produced twenty-five patents, and participated in major scientific collaborations including a project funded with 5 million yuan. As a recipient of Jiangxi’s Early-Career Young Talents Program, she continues to advance innovation in intelligent vehicle systems. She remains committed to impactful research, advancing engineering applications, and contributing to societal and technological development.

Profile : Scopus

Featured Publications

Liu, Y., & [Co-author(s) if any]. (2025). Continuous path tracking of robots based on positioning error compensation with iterative learning control. IEEE Transactions on Instrumentation and Measurement.

Florin Popister | Mechanical Engineering | Engineering Research Excellence Award

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Assoc. Prof. Dr. Florin Popister | Mechanical Engineering | Engineering Research Excellence Award

Technical University of Cluj-Napoca | Romania

Assoc. Prof. Dr. Eng. Florin Popișter is an accomplished researcher and academic in industrial engineering, mechanical design, and robotics. He earned his Ph.D. in Industrial Engineering from the Technical University of Cluj-Napoca, where he currently serves as an Associate Professor, contributing to teaching, research, and supervision in areas such as CAD/CAM systems, industrial robots, reverse engineering, and advanced manufacturing. His professional experience spans both academia and industry, including significant contributions as a design engineer at Gühring Romania, where he developed customized PCD/PCBN tools for the automotive sector. His research includes 3D printing technologies, robotic mechanisms, toolpath generation, workspace optimization, and digital manufacturing, with multiple Q1 journal publications in Polymers, Applied Sciences, and Mathematics. He has led and contributed to national and international research contracts, including H2020 Smart2 and projects focused on automation systems for the pharmaceutical industry. His achievements include a Best Paper Award, participation in Prototypes for Humanity, and invited professorships in Europe. His work continues to advance intelligent manufacturing, Industry 4.0 applications, and smart robotic systems.

Profile : Orcid

Featured Publications

Popescu, D., Dragomir, D., Popișter, F., & Dragomir, M. (2025). AI alignment to enhance production processes performance and resilience. In Book chapter. Springer.

Dragomir, M., Apolțan, D., Cioșan, A., & Popișter, F. (2025). Assessing the potential of emerging digital technologies to transform the production sector. Annals of the Academy of Romanian Scientists Series on Economy, Law and Sociology.

Popișter, F., Ciudin, P., Dragomir, M., & Goia, H. Ș. (2025). From assistive to intelligent: The development of a low-cost smart crutch system. In Book chapter. Springer.

Popișter, F. (2025). Experimental study of comprehensive performance analysis regarding the dynamical/mechanical aspects of 3D-printed UAV propellers and sound footprint. Polymers, 17(11), 1466.

Popișter, F., Goia, H. Ș., & Ciudin, P. (2025). Influence of polymers surface roughness on noise emissions in 3D-printed UAV propellers. Polymers, 17(8), 1015.