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.

Manas Ranjan Sethi | ECE | Best Researcher Award

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Mr. Manas Ranjan Sethi | ECE | Best Researcher Award

Research Scholar at NIT Silchar, India

Manas Ranjan Sethi is a dedicated academic professional currently pursuing a Ph.D. in Electronics and Instrumentation Engineering at NIT Silchar, with a strong focus on machine learning applications in fault diagnosis and energy systems. He holds an M.Tech in Electronics & Telecommunication from BPUT, Odisha and has over 12 years of teaching experience, having worked as an Assistant Professor at Gandhi Institute for Technology (GIFT) and as a Lecturer at Koustuv Institute of Self Domain, Bhubaneswar. His research interests include machine learning, signal processing, and sustainable energy systems, particularly in wind turbine diagnostics and emotion recognition using EEG signals. Manas has contributed to numerous journals, conferences, and book chapters, and he has earned distinctions such as qualifying CBSE-UGC NET and GATE. He is also skilled in technical tools, enjoys singing, and has a passion for reading.

Publication Profile : 

Scopus

 

🎓 Educational Background :

Manas Ranjan Sethi is currently pursuing a Ph.D. in Electronics and Instrumentation Engineering at NIT Silchar (since March 2020). He holds an M.Tech in Electronics & Telecommunication (Specialization in Communication Engineering) from BPUT, Odisha (2012), with a CGPA of 8.20. He completed his B.E. in Electronics & Telecommunication from BPUT, Odisha, in 2006, securing a 62.19%. Additionally, he completed his +2 Science and Matriculation from MP Board, Madhya Pradesh.

💼 Professional Experience :

Manas has a rich academic career spanning over 12 years. He served as an Assistant Professor in the Electronics & Communication Engineering Department at Gandhi Institute for Technology (GIFT), Bhubaneswar, from November 2013 to March 2020. Prior to that, he worked as a Lecturer in the Electronics & Telecommunication Engineering Department at Koustuv Institute of Self Domain, Bhubaneswar, from July 2007 to November 2013. He has a strong foundation in teaching and mentoring students in the field of Electronics and Communication Engineering.

📚 Research Interests : 

Manas’s research interests lie in the domains of Machine Learning, Signal Processing, and Fault Diagnosis. His work focuses on vibration signal-based diagnostics and energy extraction using wind turbines. He is passionate about leveraging machine learning techniques for predictive maintenance and condition monitoring. His recent research includes the application of meta-classifiers for diagnosing wind turbine blade faults and exploring emotion recognition through EEG signals.

🏆Achievements & Certifications :

Manas has earned several academic distinctions, including qualifying the CBSE-UGC NET (Electronic Science) in July 2018, and securing GATE scores of 260 (2016) and 218 (2011) in Electronics and Communication. He has also attended and contributed to various seminars, workshops, and short-term courses in fields such as VLSI Design, Microwave Filters, and Adaptive Signal Processing.

📝 Publication Top Notes :

  • Sethi, M. R., Subba, A. B., Faisal, M., Sahoo, S., & Koteswara Raju, D. (2024). Fault diagnosis of wind turbine blades with continuous wavelet transform based deep learning model using vibration signal. Engineering Applications of Artificial Intelligence, 138, 109372.
  • Sethi, M. R., Sahoo, S., Dhanraj, J. A., & Sugumaran, V. (2023). Vibration Signal-Based Diagnosis of Wind Turbine Blade Conditions for Improving Energy Extraction Using Machine Learning Approach. Smart and Sustainable Manufacturing Systems, 7(1), 14–40.
  • Chatterjee, S., Sethi, M. R., & Asad, M. W. A. (2016). Production phase and ultimate pit limit design under commodity price uncertainty. European Journal of Operational Research, 248(2), 658–667.
  • Sethi, M. R., Parhi, S. S., Sahoo, S., Sugumaran, V., & Mohanty, S. R. (2023). Fault Diagnosis of Wind Turbine Blades Through Vibration Signal Using Filtered Cultivation Data: A Comparative Study. Proceedings of the 2023 IEEE Region 10 Symposium, TENSYMP 2023.
  • Kar, P., Hazarika, J., & Sethi, M. R. (2023). A Comparative Study between Supervised and Unsupervised Techniques for Two Class Emotion Recognition using EEG. Proceedings of the 2023 IEEE 8th International Conference for Convergence in Technology, I2CT 2023.
  • Banala, H. S., Sahoo, S., Sethi, M. R., & Sharma, A. K. (2023). Fault Diagnosis in Wind Turbine Blades Using Machine Learning Techniques. In R. Doriya, B. Soni, A. Shukla, & X. Z. Gao (Eds.), Machine Learning, Image Processing, Network Security and Data Sciences (Lecture Notes in Electrical Engineering, Vol. 946), 401–411. Springer, Singapore.
  • Sethi, M. R., Sahoo, S., Kanoongo, S., & Hemasudheer, B. (2022). A Comparative Study on Diagnosing Wind Turbine Blade Fault Conditions using Rule Classifier. Proceedings of the 2022 2nd International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET 2022), 1–6. doi: 10.1109/ICEFEET51821.2022.9848401.
  • Sethi, M. R., Hemasudheer, B., Sahoo, S., & Kanoongo, S. (2022). A Comparative Study on Diagnosing Wind Turbine Blade Fault Conditions using Vibration Data through META Classifiers. Proceedings of the 2022 4th International Conference on Energy, Power, and Environment (ICEPE 2022), 1–5. doi: 10.1109/ICEPE55035.2022.9798026.