Ming Chen | Engineering | Research Excellence Award

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Dr. Ming Chen | Engineering | Research Excellence Award 

Lecturer at  Zhejiang Ocean University | China

Dr. Ming Chen is a researcher in composite structures, uncertainty quantification, and data-driven intelligent design, with a strong focus on underwater composite cylindrical shells. His work integrates numerical simulation, polynomial chaos expansion, Bayesian deep learning, symbolic regression, and automated machine learning for structural analysis, reliability assessment, and design optimization under uncertainty. He has published in leading journals including Mechanics of Advanced Materials and Structures and Journal of Marine Science and Engineering. According to Scopus, Dr. Ming Chen has 6 publications, 18 citations, and an h-index of 2. His research contributes to probabilistic machine learning frameworks, global sensitivity analysis, and digital-twin multi-fidelity modeling for advanced composite systems.

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Featured Publications

Shyamal Acharya | Engineering | Research Excellence Award

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Mr. Shyamal Acharya | Engineering | Research Excellence Award

Assistant Professor | Chittagong University of Engineering & Technology (CUET) | Bangladesh

Mr. Shyamal Acharya is an accomplished researcher and academic in Civil Engineering with a strong specialization in Water Resources Engineering, combining teaching excellence with applied research and consultancy experience. His scholarly work focuses on sustainable water management, hydrologic alteration, reservoir sedimentation, flood risk assessment, and performance evaluation of urban water supply systems, with particular relevance to the socio-economic and environmental context of Bangladesh. He has contributed peer-reviewed research published by internationally recognized publishers, addressing critical issues such as the impacts of hydraulic infrastructure on river systems and efficiency assessment of public water utilities. His research methodology integrates remote sensing, hydrological modeling, risk assessment frameworks, and institutional performance indicators to support evidence-based policy and engineering decisions. Alongside academic research, he has extensive professional experience in high-impact consultancy projects, including feasibility studies and structural design of port infrastructure, tourism development initiatives, dam stability assessments, and industrial water-related engineering solutions. His involvement in reservoir irrigation feasibility and flood mitigation studies reflects a strong commitment to climate resilience, food security, and sustainable infrastructure development. As an educator and mentor, he actively contributes to capacity building in water resources engineering and civil engineering practice. He is a Life Fellow of a national professional engineering body and maintains strong links with professional and development institutions, enabling effective knowledge transfer between academia, industry, and policy stakeholders. His profile demonstrates sustained contributions to research excellence, practical engineering impact, and national development priorities in water and environmental engineering.

Profile: Scopus

Featured Publications

Acharya, S. (2025). Performance assessment of a public water supply provider in Bangladesh. Urban Water Journal.

Gul Durak | Engineering | Best Research Article Award

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Ms. Gul Durak | Engineering | Best Research Article Award

Yildiz Technical University | Turkey

Ms. Gul Durak is an industrial engineering professional with strong applied expertise at the intersection of air cargo logistics, operations management, and cost optimization, developed through extensive practice in a global airline and manufacturing environments. Her professional focus centers on operational efficiency, air cargo logistics systems, cost analysis, and financial decision-support, combining analytical rigor with real-world logistics performance needs. She has built advanced competence in evaluating operation costs, managing logistics workflows, supporting strategic negotiations, and contributing to company-level management decisions within complex, large-scale organizations. Her experience spans air cargo operations, logistics specialization, and engineering roles that emphasize data-driven optimization and performance improvement, supported by quantitative tools and optimization software. In parallel, her research orientation reflects a growing interest in industrial engineering methodologies, logistics finance, and decision-making models that enhance efficiency and sustainability in transportation and supply chain systems. She has contributed to cost optimization initiatives recognized for their impact, demonstrating an ability to translate analytical research into actionable operational improvements. Alongside professional practice, she actively engages with academic and industry communities through invited talks and knowledge-sharing activities, highlighting her commitment to bridging theory and practice. Her skill set includes advanced logistics analytics, negotiation, financial analysis, and operations research tools, complemented by multilingual communication abilities that support international collaboration. Overall, her profile reflects a practitioner-researcher perspective, combining industrial engineering research interests with hands-on expertise in air cargo logistics and cost-focused operational strategy.

Profiles: Scopus | Orcid 

Featured Publication

Durak, G., & Çetin Demirel, N. (2025). Cargo aircraft capacity optimization: A hybrid approach comprising a genetic algorithm and large neighborhood search. Applied Sciences, 15(22), 11988.

Zhiqi Wu | Engineering | Best Researcher Award

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Ms. Zhiqi Wu | Engineering | Best Researcher Award

Student at Anhui University of Science and Technology | China

Zhiqi Wu is a Master’s student in Electrical Engineering at Anhui University of Science and Technology, specializing in computer vision applications for intelligent coal gangue detection. His research emphasizes developing lightweight, high-performance models that improve automation and efficiency in mining operations. Zhiqi proposed a novel model integrating multispectral imaging with knowledge distillation, achieving a precision increase of up to 6% while reducing model size by 21.8%, enabling deployment on mobile and edge devices for real-time sorting. This approach advances intelligent coal industry practices by combining computational efficiency with practical industrial applicability. Zhiqi’s work exemplifies the translation of advanced AI techniques into actionable solutions for industrial automation, with a focus on scalability, accuracy, and sustainability. His contributions are recognized in the research community, with 1 citation for his published work, highlighting its impact and relevance. To date, he has contributed to 4 documents in his research portfolio, reflecting his engagement in ongoing innovation and knowledge dissemination. While his h-index currently stands at 1, it represents a promising start in a career dedicated to applied AI in mining technologies. Zhiqi continues to explore methods for optimizing computer vision systems in industrial contexts, advancing automation, operational safety, and resource efficiency. His work bridges theoretical research and practical deployment, positioning him as an emerging researcher making measurable contributions to intelligent mining technologies.

Profile: Scopus

Featured Publications

Yan, P. (2025). Transformer fault diagnosis based on LIF technology and COA-GRU algorithm. Engineering Research Express, 7(2), 25409.