Rate My Professor Ji Jinn

Foo's research focuses on novel heat transfer methods that employ insert-induced fluid flow fluctuations for thermal dissipation via forced convective or natural convective heat transfer. A key aspect of his work involves using planar fractal geometry to generate turbulence, capitalizing on its ability to produce higher turbulence intensities and rescalable flow frequencies across various characteristic length scales, thereby enhancing diffusivity, mixing, and transport of mass, momentum, and energy. His group investigates grid inserts to augment heat transfer, with projects funded by the Malaysian Ministry of Higher Education's Fundamental Research Grant Scheme and in collaboration with Daikin R&D. Selected publications include "Augmentation of piezoelectric thin-film flapping velocimetry turbulence strength detection via machine learning" (2025), "Heat transfer performance and fouling analysis of clove-treated graphene nanoplatelet nanofluid in a double-pipe heat exchanger" (2025), "Lattice Boltzmann-based microchannel concentration mixing with surface roughness-mediated flow dynamics" (2025), "A Computational Study on the Use of Phase Shift to Improve Dual-frequency Sonothrombolysis Outcomes" (2024), "Comparisons of Sequential and Simultaneous Acid–Base Injections During Thermochemical Ablation: A Computational Study" (2024), "Fractal cube-induced homogenisation of dual concentration microchannel flow in transitional Re: Lattice Boltzmann modelling" (2024), and "Fractal grid-induced turbulence strength characterization via piezoelectric thin-film flapping velocimetry" (2021).