Mehabaw Fikrie Yehuala |  Computaional Physics | Best Researcher Award

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Mr. Mehabaw Fikrie Yehuala |  Computaional Physics | Best Researcher Award

Chief Academic Technical Assistant | University of Gondar | Ethiopia

Mr. Mehabaw Fikrie Yehuala is an emerging researcher and academic professional specializing in Computational Physics, with an active role as Chief Academic Technical Assistant at the University of Gondar. His career reflects a deep commitment to advancing Computational Physics through theoretical modeling, simulation techniques, and practical implementation in modern physical systems. His research expertise centers on Computational Physics applications in material dynamics, phase separation, and simulation-based investigations, particularly focusing on systems involving complex mixtures and energy interactions. Through his scholarly journey, Mr. Mehabaw has demonstrated a rigorous approach to Computational Physics, integrating programming proficiency in Python, Fortran, and LaTeX with analytical frameworks to model and interpret physical phenomena. His publication in Separation Science and Technology stands as a key contribution to the scientific community, highlighting the relevance of Computational Physics in studying the phase separation of oil–water mixtures using Monte Carlo simulation methods. His collaborative research embodies an interdisciplinary essence, bridging experimental insights with the predictive strength of Computational Physics. Mr. Mehabaw’s professional engagement extends beyond research into educational innovation, where he has contributed significantly to the development of physics laboratory manuals and academic resource materials, further strengthening the pedagogical aspects of Computational Physics education. His recognition for academic excellence and active participation in institutional development underscores his leadership and dedication to the advancement of scientific knowledge. As an analytical thinker and a collaborative scientist, Mr. Mehabaw continues to explore new dimensions in Computational Physics, contributing to both academic and societal progress. His vision emphasizes fostering research-driven learning environments and leveraging Computational Physics methodologies to address real-world scientific and industrial challenges, marking him as a promising contributor to the global physics and research community.

Profile: ORCID

Featured Publication

1. Fikrie, M., Birhanu, T., Bassie, Y., Abebe, Y., & Temare, Y. (2025). Investigation of phase separation of mixture of oil and water in Monte Carlo simulation. Separation Science and Technology.

Prof. Dr. Jinju Sun | Computational Methods | Best Researcher Award

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Prof. Dr. Jinju Sun | Computational Methods | Best Researcher Award

Professor | Xi'an Jiaotong University | China

Prof. Dr. Jinju Sun is a distinguished scholar in the School of Energy and Power Engineering at Xi’an Jiaotong University, renowned for her pioneering contributions to fluid mechanics, turbomachinery, and multiphase flow systems through advanced Computational Methods. Her educational journey spans cryogenic engineering to a PhD in turbomachinery and engineering mechanics, which laid the foundation for her expertise in Computational Methods applied to turbomachinery optimization, Lattice Boltzmann modeling, and Vortex Method simulations. Throughout her professional career, she has served as a researcher, lecturer, and professor, advancing research through numerous national and international collaborations emphasizing Computational Methods in fluid dynamics and green energy system design. She has received prestigious honors, including the Donald Julius Groen Prize and the Arthur Charles Main Award from the Institution of Mechanical Engineers (UK), in recognition of her outstanding achievements utilizing Computational Methods for energy system modeling and flow optimization. Her research interests include cryogenic liquid turbines, compressor instabilities, and innovative Computational Methods for fluid-structure interaction and multiphase flow behavior. She has authored numerous high-impact publications and holds multiple international patents that demonstrate her excellence in Computational Methods-based innovation. Prof. Dr. Jinju Sun’s research skills encompass CFD modeling, LBM, topology optimization, and Computational Methods-driven analysis for turbomachinery and green energy systems. In conclusion, her dedication to advancing Computational Methods in engineering has positioned her as a global leader driving innovation, sustainability, and scientific excellence in modern energy and power engineering.

Profile: ORCID

Featured Publications

1. Qu, Y., Sun, J., Song, P., & Wang, J. (2025). Enhancing efficiency and economic viability in Rectisol system with cryogenic liquid expander. Asia-Pacific Journal of Chemical Engineering.

2. Ge, Y., Peng, J., Chen, F., Liu, L., Zhang, W., Liu, W., & Sun, J. (2023). Performance analysis of a novel small-scale radial turbine with adjustable nozzle for ocean thermal energy conversion. AIP Advances.

3. Fu, X., & Sun, J. (2023). Three-dimensional color-gradient lattice Boltzmann model for simulating droplet ringlike migration under an omnidirectional thermal gradient. International Journal of Thermal Sciences.

4. Song, P., Sun, J., Wang, S., & Wang, X. (2022). Multipoint design optimization of a radial-outflow turbine for Kalina cycle system considering flexible operating conditions and variable ammonia-water mass fraction. Energies.

5. Song, P., Wang, S., & Sun, J. (2022). Numerical investigation and performance enhancement by means of geometric sensitivity analysis and parametric tuning of a radial-outflow high-pressure oil–gas turbine. Energies.

Dr. Bin Song | Experimental Methods | Best Researcher Award

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Dr. Bin Song | Experimental Methods | Best Researcher Award

Associate Professor | Southwest Petroleum University | China

Dr. Bin Song, an accomplished scholar in Experimental Methods, holds a Doctor of Engineering and serves as an Associate Researcher and Master’s Supervisor at Southwest Petroleum University. His work in Experimental Methods has greatly advanced gas safety and integrity assessment, hydrogen storage and transportation, and efficient utilization processes. Through his innovative use of Experimental Methods, he has produced over twenty high-level publications, sixteen of which are SCI-indexed, demonstrating his consistent excellence in research dissemination. His involvement in Experimental Methods also extends to securing four national invention patents, one of which achieved successful technological transformation, showcasing his strong applied research capabilities. Furthermore, he has contributed to the compilation of two industry and township standards, reinforcing the practical impact of his Experimental Methods-based investigations. His recognition in the scientific community stems from his ability to integrate Experimental Methods with engineering innovation, improving safety, performance, and sustainability in petroleum and hydrogen systems. His analytical expertise, technical precision, and interdisciplinary collaboration highlight his strong research skills and commitment to advancing Experimental Methods for industrial and academic excellence. Dr. Bin Song continues to inspire future researchers through his dedication to innovation, knowledge transfer, and technological development in Experimental Methods-driven research. 207 Citations, 18 Documents, 7 h-index.

Profile: Scopus

Featured Publication

1. Novel method for optimizing emergency response facility layouts in gas pipeline networks. (2025). Journal of Pipeline Systems Engineering and Practice.