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.

Salomon Dominique Edimo Kingue | Engineering | Research Excellence Award

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Mr. Salomon Dominique Edimo Kingue | Engineering | Research Excellence Award

State University of Campinas | Brazil

Mr. Salomon Dominique Edimo Kingue is a reservoir engineer and researcher specializing in enhanced oil recovery (EOR), reservoir simulation, and sustainable subsurface energy strategies. His expertise centers on FAWAG/WAG processes, CO₂ storage modeling, and integrated reservoir–production optimization for complex carbonate systems, particularly within Brazilian pre-salt environments. He is highly skilled in using CMG (IMEX, STARS, GEM, CMOST), Petrel, Python, and advanced analytical tools to investigate flow behavior, improve recovery efficiency, and reduce greenhouse gas emissions. His research spans numerical simulation of EOR mechanisms, uncertainty analysis, carbon capture and storage (CCS), fractured-vuggy reservoir upscaling, and evaluation of production potential in hydrocarbon basins. He has co-authored studies on underground LPG storage and reservoir performance prediction, and contributed to interdisciplinary projects involving major industry partners. His work also extends to geological interpretation, multidisciplinary collaboration, and scientific communication through symposiums, poster sessions, and peer-reviewed publications. Salomon combines strong analytical reasoning with leadership, teamwork, and effective communication, reflecting his commitment to innovation-driven reservoir management and the advancement of low-carbon energy solutions.

Profile: Orcid

Featured Publications

Kingue, S. D. E., Akinmuda, O. B., Kuiekem, D., & Djitchouang, G. L. (2025). Assessing the production potential of Niger Delta reservoirs under uncertainty using numerical simulation tools. Petroleum Science and Technology.

Kuiekem, D., Kingue, S. D. E., Boroh, W., Noupa, R. K., Matateyou, J., & Ngounouno, I. (2025). Simulation study of underground LPG storage in a depleted conceptual oil reservoir. Petro Chem Indus Intern, 8(2), 1–14.

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.

Ashish Ranjan Dash | Engineering | Best Researcher Award

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Dr. Ashish Ranjan Dash | Engineering | Best Researcher Award

Associate Professor at Centurion University of Technology and Management | India

Dr. Ashish Ranjan Dash is a highly accomplished academic and researcher in the field of electrical engineering, specializing in power electronics, multilevel inverters, and power quality improvement. With a proven track record in research, teaching, and project leadership, he has significantly contributed to advancements in smart infrastructure, renewable energy systems, and IoT-enabled agricultural automation. He has also played a pivotal role in supervising doctoral students, developing innovative solutions for industrial applications, and leading consultancy projects for technology-driven agriculture and smart systems.

Publication Profile 

Scopus

Google Scholar

Educational Background 

Dr. Dash earned his Ph.D. in Power Electronics from the National Institute of Technology (NIT) Rourkela, focusing on cascaded multilevel inverter-based shunt active filters under varying grid voltage conditions. He also holds an M.Tech. in Power Control and Drives from NIT Rourkela, where his dissertation explored control strategies for grid-connected inverter systems during fault conditions. His academic foundation is further strengthened by a B.Tech. in Electrical Engineering and a Diploma in Electrical Engineering, complemented by a strong record of academic excellence throughout his studies.

Professional Experience 

With over a decade of academic and research experience, Dr. Dash serves as an Associate Professor at Centurion University of Technology and Management, Odisha. His prior roles include research and academic positions in engineering colleges and at the Council of Scientific and Industrial Research. He has held key administrative positions such as Dean and Associate Dean of the School of Engineering and CEO of the Smart Infrastructure Research Center, where he has led interdisciplinary projects integrating IoT, automation, and renewable energy systems.

Research Interests 

His research focuses on power electronics, multilevel inverter design, power quality enhancement, electric vehicle charging infrastructure, smart grid systems, and IoT-enabled automation. He also works extensively on agricultural automation, including polyhouse automation, speed breeding chambers, and plant phenotyping systems. Emerging interests include machine learning applications for plant disease detection, robotics, and smart farming technologies.

Awards and Honors 

Dr. Dash has received multiple accolades, including the Distinguished Achiever Award at the Provost Research Awards and recognition as a session chair at IEEE international conferences. He is the founder of a technology-driven startup and actively engages in professional communities such as the IEEE Power Electronics Society, IEEE Industry Applications Society, and IEEE SIGHT.

Research Skills 

He possesses strong expertise in the design, modeling, and implementation of cascaded multilevel inverters, power quality control algorithms, and renewable energy integration. His skills extend to IoT-based system design, automation technologies, electric vehicle charging systems, and cloud-based agricultural monitoring. He is also an experienced reviewer for several high-impact international journals in power electronics and smart grid applications.

Publications 

A unified control of grid-interactive off-board EV battery charger with improved power quality

Citations: 49

Year: 2022

Reactive power compensation using vehicle-to-grid enabled bidirectional off-board EV battery charger

Citations: 34

Year: 2021

Adaptive LMBP training‐based icosϕ control technique for DSTATCOM

Citations: 33

Year: 2020

Analysis of PI and PR controllers for distributed power generation system under unbalanced grid faults

Citations: 33

Year: 2011

Design and implementation of a cascaded transformer coupled multilevel inverter‐based shunt active filter under different grid voltage conditions

Citations: 24

Year: 2019

Conclusion 

Dr. Ashish Ranjan Dash is a forward-looking researcher and educator whose work bridges advanced power electronics with practical applications in smart infrastructure and agricultural automation. His multidisciplinary expertise, leadership in funded projects, and dedication to mentoring the next generation of engineers make him a valuable contributor to both academia and industry. His continued research promises innovative advancements in electric mobility, renewable energy integration, and intelligent automation systems.

Ikhlef JEBBOR | Industrial engineering | Excellence in Research

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Dr. Ikhlef JEBBOR | Industrial engineering | Excellence in Research

ibn Tofail University at National School of Applied Sciences, Ibn Tofail University, Kenitra, Morocco

A Ph.D. candidate in Sustainable Optimization of Manufacturing and Supply Chain with extensive experience in both academia and industry. Focuses on lean manufacturing, production optimization, and AI for sustainable development. Currently an Engineering Project Leader at Sumitomo Electric Wiring Systems (SEWS-E), leading process improvements in the automotive industry. Expert in project management, operational research, and continuous improvement strategies such as Six Sigma and Kaizen. Has published numerous peer-reviewed articles and presented at international conferences on sustainability and advanced manufacturing techniques.

Professional Profile

Scopus Profile

Education:

  • Ph.D. in Sustainable Optimization of Manufacturing and Supply Chain (ENSA Kenitra, Ibn Tofail University, 2022 – Current)
  • State Engineer, Industrial Engineering (GI) (FST Errachidia, Moulay Ismail University, 2010 – 2013)
  • Physics & Chemistry Teacher Education Diploma (CPR Mohamed V SAFI, Morocco, 2009 – 2010)
  • Professional University Degree, Renewable Energies and Sustainable Development (ERDD) (Faculty of Sciences -Agadir, Ibn Zohr University, 2007 – 2009)
  • General University Degree, Physical Matter Sciences (SMP) (Faculty of Sciences -Agadir, Ibn Zohr University, 2005 – 2007)
  • BAC, Experimental Science (Salah Eddin Elayyoubi High School, Tinghir, 2005)

Professional Experience:

Sumitomo Electric Wiring Systems (SEWS-E)

  • Engineering Project Leader (Feb 2021 – Current)
  • Senior Project Engineer (Aug 2018 – Jan 2021)
  • Process Engineer (Sep 2015 – Aug 2018)
  • Work Study Engineer (May 2014 – Aug 2015)

Research Interests:

  • Facilities Design and Optimization
  • Lean Manufacturing
  • Production Planning and Scheduling
  • Supply Chain Management
  • Mathematical Modeling and Optimization

Awards and Honors:

  • Outstanding Project Leader Award
    Sumitomo Electric Wiring Systems (SEWS-E), 2022
    Recognized for leading key process improvements in automotive production, significantly enhancing efficiency and innovation.
  • Excellence in Lean Manufacturing Implementation
    Sumitomo Electric Wiring Systems (SEWS-E), 2020
    Awarded for implementing lean manufacturing strategies that resulted in significant cost savings and production efficiency.
  • Best Paper Award
    International Conference on Industrial Engineering and Applications (ICIEA), 2023
    Awarded for presenting the paper on “Improvement of an Assembly Line in the Automotive Industry: A Case Study in Wiring Harness Assembly Line.”
  • Research Excellence Award
    ENSA Kenitra, Ibn Tofail University, 2022
    For contributions to sustainable optimization of manufacturing and supply chain research, particularly in the automotive industry.
  • Innovation Award for Sustainable Practices
    Sustainability and Advanced Manufacturing Techniques Conference, 2023
    Honored for innovative research in applying AI and optimization techniques for sustainable manufacturing practices.

Conclusion:

With an extensive background in industrial engineering, lean manufacturing, and AI applications, I have consistently delivered impactful results in both academia and industry. My experience as an Engineering Project Leader at Sumitomo Electric Wiring Systems (SEWS-E) and my ongoing doctoral research on the sustainable optimization of manufacturing and supply chain systems equip me with a strong foundation for tackling complex industry challenges.

Through my research, publications, and practical experience, I aim to contribute to the development of more efficient, sustainable, and innovative manufacturing processes. I am committed to driving continuous improvement through the application of cutting-edge methodologies such as Six Sigma, Kaizen, and AI-driven optimizations. As I continue to advance in both academia and industry, I strive to shape the future of sustainable industrial engineering and contribute to global efforts for sustainable development.

Publication Top Notes

  1. 📊 Article: Forecasting supply chain disruptions in the textile industry using machine learning: A case study
    • Authors: Jebbor, I., Benmamoun, Z., Hachimi, H.
    • Journal: Ain Shams Engineering Journal, 2024, 15(12), 103116
    • Citations: 1
  2. 🌍 Conference Paper: Optimization of Carbon Emissions in Asphalt Pavement Construction
    • Authors: Benmamoun, Z., Elkhechafi, M., Abdo, A.A., Jebbor, I.
    • Conference: 10th Edition of the International Conference on Optimization and Applications, ICOA 2024 – Proceedings
    • Citations: 0
  3. 🧠 Conference Paper: Comparison of Generative AI Models in Supply Chain Management: Benefits, Applications and Challenges
    • Authors: Khlie, K., Benmamoun, Z., Jebbor, I., Hachimi, H.
    • Conference: 10th Edition of the International Conference on Optimization and Applications, ICOA 2024 – Proceedings
    • Citations: 0
  4. 🤖 Article: Generative AI for enhanced operations and supply chain management
    • Authors: Khlie, K., Benmamoun, Z., Jebbor, I., Serrou, D.
    • Journal: Journal of Infrastructure, Policy and Development, 2024, 8(10), 6637
    • Citations: 1
  5. 🌱 Article: Revolutionizing cleaner production: The role of artificial intelligence in enhancing sustainability across industries
    • Authors: Jebbor, I., Benmamoun, Z., Hachmi, H.
    • Journal: Journal of Infrastructure, Policy and Development, 2024, 8(10), 7455
    • Citations: 1
  6. 📉 Article: Leveraging variational autoencoders and recurrent neural networks for demand forecasting in supply chain management: A case study
    • Authors: Khlie, K., Benmamoun, Z., Fethallah, W., Jebbor, I.
    • Journal: Journal of Infrastructure, Policy and Development, 2024, 8(8), 6639
    • Citations: 5
  7. 📚 Conference Paper: Application of Fuzzy Logic for Evaluating Student Learning Outcomes in E-Learning
    • Authors: Mousse, M.A., Almufti, S.M., García, D.S., Aljarbouh, A., Tsarev, R.
    • Conference: Lecture Notes in Networks and Systems, 2024, 935 LNNS, pp. 175–183
    • Citations: 2
  8. 🚗 Conference Paper: Application of Manufacturing Cycle Efficiency to Increase Production Efficiency: Application in Automotive Industry
    • Authors: Jebbor, I., Benmamoun, Z., Hachimi, H.
    • Conference: 2024 4th International Conference on Innovative Research in Applied Science, Engineering and Technology, IRASET 2024
    • Citations: 3
  9. 🔧 Conference Paper: Process Improvement of Taping for an Assembly Electrical Wiring Harness
    • Authors: Jebbor, I., Raouf, Y., Benmamoun, Z., Hachimi, H.
    • Conference: Lecture Notes in Business Information Processing, 2024, 507 LNBIP, pp. 35–48
    • Citations: 3
  10. ⚙️ Article: Optimizing Manufacturing Cycles to Improve Production: Application in the Traditional Shipyard Industry
  • Authors: Jebbor, I., Benmamoun, Z., Hachimi, H.
  • Journal: Processes, 2023, 11(11), 3136
  • Citations: 10