Ismail Adewale Olumegbon

University of Maryland Baltimore County

Research Expertise

Atmospheric science
Machine learning
Computational physics
Renewable Energy, Sustainability and the Environment
Energy Engineering and Power Technology
Electrical and Electronic Engineering
Condensed Matter Physics
Atomic and Molecular Physics, and Optics
Fluid Flow and Transfer Processes
Mechanical Engineering
Electronic, Optical and Magnetic Materials
Physical and Theoretical Chemistry
Materials Chemistry
Spectroscopy
Instrumentation
Applied Mathematics
Control and Systems Engineering
Artificial Intelligence

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Publications

On the assessment of specific heat capacity of nanofluids for solar energy applications: Application of Gaussian process regression (GPR) approach
Journal of Energy Storage
2021
On the specific heat capacity estimation of metal oxide-based nanofluid for energy perspective – A comprehensive assessment of data analysis techniques
International Communications in Heat and Mass Transfer
2021
On the Thermal Conductivity Assessment of Oil-Based Hybrid Nanofluids using Extended Kalman Filter integrated with feed-forward neural network
International Journal of Heat and Mass Transfer
2021
Specific heat capacity of molten salt-based nanofluids in solar thermal applications: A paradigm of two modern ensemble machine learning methods
Journal of Molecular Liquids
2021
Estimating the density of hybrid nanofluids for thermal energy application: Application of non-parametric and evolutionary polynomial regression data-intelligent techniques
Measurement
2022
Lattice constant prediction of A2XY6 cubic crystals (A = K, Cs, Rb, TI; X = tetravalent cation; Y = F, Cl, Br, I) using computational intelligence approach
Journal of Applied Physics
2020
Near-infrared (NIR) spectroscopic evaluation of articular cartilage: A review of current and future trends
Applied Spectroscopy Reviews
2016
Characterizing human subchondral bone properties using near-infrared (NIR) spectroscopy
Scientific Reports
2018
Modelling the viscosity of carbon-based nanomaterials dispersed in diesel oil: a machine learning approach
Journal of Thermal Analysis and Calorimetry
2021
Development of machine learning models for the prediction of binary diffusion coefficients of gases
Engineering Applications of Artificial Intelligence
2023
Scattering Matrix and Observables in Scattering and Decays
Quantum Physics
2013
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