Dr. Ghulam Rasool is an Assistant Research Professor at Prince Mohammad Bin Fahd University, KSA, with a Ph.D. in Fluid Mechanics from Zhejiang University, a globally ranked top 50 institution. His expertise lies in the areas of Applied Mathematics, fluid mechanics, computational fluid dynamics (CFD), Energy Storage and optimization for renewable energy applications. With a strong background in nanotechnology, entropy analysis, and heat transfer, his research focuses on Latent Heat Thermal Energy Storage (LHTES) using nano-enhanced phase change materials (Nano-PCMs) and hybrid nanofluids for sustainable energy solutions. He has held academic and research positions across China, Morocco, USA, Lebanon, Saudi Arabia, and Pakistan, including roles as Senior Researcher at Beijing University of Technology, Postdoctoral Fellow at Lebanese American University, and Assistant Professor at Wuxi University, China. Dr. Rasool has led and contributed to multiple high-impact international research projects, including grants from the High Talent International Researchers Fund, Beijing Natural Science Foundation Fund, and Young Foreign Expert Project Fund by the Ministry of Science and Technology of China. His work has been recognized with prestigious awards such as the Top Cited Article Award and Wuxi Friendship Ambassador Award. As a Member of the American Society of Thermal and Fluid Engineers (ASTFE) and the American Mathematical Society (AMS), he actively contributes to the scientific community. He serves as an Academic Editor for PLOS One, Heliyon, Advances in Materials Science and Engineering, and Advances in Mathematical Physics, and as a Topical Advisory Panel Member at MDPI. Additionally, he reviews for leading journals such as Energy, Applied Thermal Engineering, and the International Journal of Heat and Mass Transfer. Dr. Rasool has presented his research at prestigious international conferences and has organized academic events, including the Seminar on Recent Trends in Fluid Mechanics at Beijing University of Technology. His expertise extends to AI-based modeling, machine learning-driven optimization, and multi-scale energy simulations, with proficiency in Mathematica, COMSOL Multiphysics, MATLAB Simulink, and other computational tools.