Mr. John de Britto Chinnappan | Computer Science | Editorial Board Member

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Mr. John de Britto Chinnappan | Computer Science | Editorial Board Member

Saveetha Engineering College| India

Dr. C. John De Britto is a dedicated researcher in Electrical and Electronics Engineering with a strong focus on power electronics, renewable energy systems, electric drives, optimization algorithms, and intelligent control strategies. His research work explores innovative solutions for improving power quality, enhancing the efficiency of renewable energy integration, and advancing smart energy systems. With contributions spanning image enhancement techniques, hybrid renewable systems, DC–DC converter architectures, electric vehicle impact mitigation, and intelligent control for photovoltaic systems, he brings a multidisciplinary approach bridging conventional power engineering with modern computational intelligence. His scholarly output includes 14 Scopus-indexed documents that have collectively received 40 citations with an h-index of 4 on Scopus. Additionally, his Google Scholar profile reflects 50 citations, an h-index of 4, and an i10-index of 1, highlighting the growing influence and visibility of his work. His publications demonstrate a strong commitment to developing sustainable engineering solutions, especially in areas such as quasi Z-source converters, hybrid renewable energy design, embedded platforms, fault recognition in industrial motors, and bio-inspired optimization for control systems. Dr. De Britto’s research impact is evident across peer-reviewed journals, international conferences, and interdisciplinary collaborations, with several studies addressing modern challenges such as electric vehicle charging impacts, microgrid performance, and automation for safety-critical applications. His continuous contributions to energy systems, computational approaches, and power conversion technologies position him as an emerging academic voice in renewable and intelligent power engineering research.

Profile

Scopus | ORCID | Google Scholar

Featured Publications

Venkatesh, S., De Britto, C. J., Subhashini, P., & Somasundaram, K. (2022). Image enhancement and implementation of CLAHE algorithm and bilinear interpolation. Cybernetics and Systems, 1–13.

Pradeep, M., Sathishkumar, S., & Subramanian, A. T. S. (2019). Recognition of fault and security of three phase induction motor by means of programmable logic controller. IOP Conference Series: Materials Science and Engineering, 623, 012017.

Yuvaraj, T., Prabaharan, N., De Britto, C. J., Thirumalai, M., Salem, M., & others. (2024). Dynamic optimization and placement of renewable generators and compensators to mitigate electric vehicle charging station impacts using the spotted hyena optimization algorithm. Sustainability, 16(19), 8458.

De Britto, C. J., Nagarajan, S., & Kumar, R. S. (2023). Effective design and implementation of hybrid renewable system using convex programming. International Journal of Green Energy, 20(13), 1473–1487.

De Britto, C. J., & Nagarajan, S. (2018). High performance quasi Z-source resonant converter with hybrid energy resources for rural electrification. International Journal of Engineering and Advanced Technology, 8(2C2), 132–135.

Mr. Ibra Fall | Computational Fluid Dynamics | Best Researcher Award

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Mr. Ibra Fall | Computational Fluid Dynamics | Best Researcher Award

Mr. Ibra Fall | PhD | National Research Center of Pumps | China

Dr. Fall Ibra is a Senegalese researcher specializing in Power Engineering, Thermo-Physics, and Computational Fluid Dynamics (CFD). His research encompasses applied fluid mechanics, multiphase flow theory, hydraulic design, and numerical simulation of gas–liquid two-phase flow systems. His work focuses on exploring the hydrodynamic mechanisms, energy conversion efficiency, and entropy generation in rotodynamic multiphase pumps and related systems. With a strong background in CFD, population balance modeling, and machine learning applications in fluid dynamics, he integrates computational modeling with experimental data to analyze flow structures, cavitation phenomena, and energy performance under complex multiphase conditions. His contributions extend to deep-sea oil and gas transport, hydraulic stability of pumping systems, and advanced turbulence modeling for gas–liquid interactions. Dr. Ibra has published extensively in high-impact journals such as Physics of Fluids, Alexandria Engineering Journal, Chaos, Solitons and Fractals, and Engineering Applications of Computational Fluid Mechanics. He has also presented his work at international symposiums on cavitation and multiphase flow. According to Scopus, Dr. Fall Ibra has authored 10 documents, cited by 49 other publications, with an h-index of 4. His Google Scholar profile similarly reflects a growing citation record and international research visibility.

Publication Profile

Scopus

Featured Publications

Falla, I., Geng, L., Gao, Y., Appiah, D., Ali, A., & Zhang, D. (2025). Effect of bubble coalescence and breakup on entropy generation in rotodynamic multiphase flow pumps. Physics of Fluids.

Falla, I., Geng, L., Gao, Y., Appiah, D., Ali, A., & Zhang, D. (2025). Numerical investigation of CFD-PBM coupled air–water flow in pipes under varying flow regimes. Alexandria Engineering Journal.

Shah, F., Falla, I., & Zhang, D. (2025). Experimental and CFD evaluation of bubble diameter and turbulence model influence on nonlinear flow dynamics. Chaos, Solitons and Fractals.

Ali, A., Yuan, J., Si, Q., & Falla, I. (2024). Comprehensive analysis of unsteady two-phase flow patterns in multiphase flow models. Engineering Applications of Computational Fluid Mechanics.

Gao, Y., Geng, L., Verdin, P. G., Falla, I., Zhang, R., Tian, Z., & Zhang, D. (2023). Modeling of dual-factor drag correction for bubbly flow under elevated pressures. Chemical Engineering and Technology.

Prof. Dr. Cesar Hernando Valencia Niño | Evolutionary Computation | Best Researcher Award

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Prof. Dr. Cesar Hernando Valencia Niño | Evolutionary Computation | Best Researcher Award

Prof. Dr. Cesar Hernando Valencia Niño | Director of Master on Data Analytics and Intelligent Systems | Santo Tomas University Bucaramanga | Colombia

Cesar Hernando Valencia Niño is a distinguished researcher in artificial intelligence, robotics, mechatronics, and intelligent control systems. His work integrates machine learning algorithms with mechanical and electrical engineering to develop predictive, inferential, and adaptive systems applied to robotics, biomedical devices, industrial automation, and human–machine interaction. As leader of a Category A research group, he has contributed significantly to interdisciplinary applications of AI in areas such as prosthetics, echo state networks, autonomous systems, and biomedical forecasting. His portfolio includes contributions to the advancement of industrial robotics, machine design, neuroevolutionary computation, magnetorheological systems, and control architectures for UAVs and prosthetics. With active participation in 25 research and innovation projects, he has produced 17 peer-reviewed journal articles, 5 book chapters, 12 industrial prototypes, 7 documented innovations, and 5 patents. He is also a recognized reviewer of top-tier indexed journals and has directed theses across undergraduate to doctoral levels. Valencia Niño has presented his work in more than 30 knowledge dissemination events, demonstrating strong engagement in academic and scientific communities. His citation impact reflects growing international recognition: Scopus reports 45 citations from 44 documents with 17 indexed publications and an h-index of 4, while Google Scholar attributes 96 citations, an h-index of 6, and an i10-index of 2. His research continues to bridge artificial intelligence with engineering solutions for complex, real-world challenges, emphasizing innovation, automation, and intelligent system design.

Publication Profile

Scopus | ORCID | Google Scholar

Featured Publications

  • Valencia, C. H., Vellasco, M. M. B. R., & Figueiredo, K. (2023). Echo State Networks: Novel reservoir selection and hyperparameter optimization model for time series forecasting. Neurocomputing, 545, 126317.

  • Valencia Niño, C. H. (2011). Modelo de optimización en la gestión de inventarios mediante algoritmos genéticos. ITECKNE: Innovación e Investigación en Ingeniería, 8(2), 156–162.

  • Valencia, C. H., Vellasco, M. M. B. R., & Figueiredo, K. T. (2014). Trajectory tracking control using echo state networks for the CoroBot’s arm. In Robot Intelligence Technology and Applications 2.

  • Valencia, C. H., Vellasco, M., Tanscheit, R., & Figueiredo, K. T. (2015). Magnetorheological damper control in a leg prosthesis mechanical. In Robot Intelligence Technology and Applications 3.

  • Valencia Niño, C. H., & Dutra, M. S. (2010). Estado del arte de los vehículos autónomos sumergibles alimentados por energía solar. ITECKNE, 7(1), 46–53.