Moshood Onifade
Associate Professor, Mining Engineering
Campus
Biography
Moshood Onifade is an Associate Professor at the Institute of Innovation, Science and Sustainability, Federation University Australia. He has been recognized as a leading expert in mining engineering and his relevance in mining has been highlighted with support from the Coaltech Research Association of South Africa.
Moshood has published over 80 peer-reviewed research papers in high-impact journals. His publishing background reflects his national and international standing and international engagement with a variety of researchers, industry, and stakeholders. Moshood has attracted several grants and awards, and he is a reviewer of scientific papers for different internationally accredited journals.
He is a Fellow of the Southern African Institute of Mining and Metallurgy (SAIMM), a registered engineer of the Council for the Regulation of Engineers in Nigeria (COREN) and a member of different professional associations. Dr. Onifade has proven to be an academic with extremely high working standards and an excellent track record.
Google Scholar: https://scholar.google.com/citations?user=4voZX_EAAAAJ&hl=en
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- Publications
An optimized machine learning framework for prediction of coal abrasive index: Leveraging supervised learning, metaheuristic optimization, and interpretability analysis
- Journals
- DOI reference: 10.1016/j.fuel.2025.136065
Plugging the gaps: Sustainable resource policy and revenue leakages in Nigeria's small-scale lithium mining
- Journals
- DOI reference: 10.1016/j.exis.2025.101788
A novel grey relational analysis-based committee of machine learning methods for enhanced prediction of coal calorific value
- Journals
- DOI reference: 10.1016/j.fuel.2025.137070
Prediction of HGI of South African coalfields: a comparative application of ANN, SVR and LSTM models
- Journals
- DOI reference: 10.1080/19392699.2024.2339319
Enhancing gas drainage and ventilation efficiency in underground coal mines: A hybrid expert decision approach for booster fan prioritization
- Journals
- DOI reference: 10.1016/j.tust.2024.106153
Predicting the hardgrove grindability index using interpretable decision tree-based machine learning models
- Journals
- DOI reference: 10.1016/j.fuel.2024.133953
Dynamic Simulation of Heat Distribution and Losses in Cement Kilns for Sustainable Energy Consumption in Cement Production
- Journals
- DOI reference: 10.3390/su17020553
Geological and geotechnical challenges on the Great Dyke of Zimbabwe and their impact on hardrock pillar design
- Journals
- DOI reference: 10.1002/dug2.70024
Intelligent Decision Framework for Booster Fan Optimization in Underground Coal Mines: Hybrid Spherical Fuzzy-Cloud Model Approach Enhancing Ventilation Safety and Operational Efficiency
- Journals
- DOI reference: 10.3390/machines13050367
Optimized Slope Stability Assessment Using an Intuitionistic Fuzzy MCDM Approach for LEM Model Selection
- Journals
- DOI reference: 10.1007/s10706-025-03164-5
Reflections on destress blasting for deep level hardrock mining: Key considerations for successful application of the techniques
- Journals
- DOI reference: 10.17159/2411-9717/3686/2025
Evaluating destress blasting for rock fracture and rockburst prediction in deep level hardrock mining
- Journals
- DOI reference: 10.17159/2411-9717/3685/2025
Evaluating the creditworthiness of a viable artisanal and small-scale mining operation
- Journals
- DOI reference: 10.17159/2411-9717/3627/2025
Deep learning-powered rock mass classification: Predicting RMR from Q-system parameters with high accuracy
- Journals
- DOI reference: 10.1016/j.rockmb.2025.100219
Modeling the Abrasive Index from Mineralogical and Calorific Properties Using Tree-Based Machine Learning: A Case Study on the KwaZulu-Natal Coalfield
- Journals
- DOI reference: 10.3390/mining5030048
Study on functional group evolution mechanisms and chemical kinetics during gas coal oxygen-free pyrolysis: Insights from high-temperature in-situ FTIR
- Journals
- DOI reference: 10.1016/j.jclepro.2025.146801
Advanced machine learning for pillar stress prediction and design optimisation in hardrock platinum mining: enhancing safety and sustainability on the Great Dyke of Zimbabwe
- Journals
- DOI reference: 10.1007/s40948-025-00990-y
Optimising tunnel support design with machine learning models
- Journals
- DOI reference: 10.1007/s12665-025-12573-x
Optimising ground support for mine tunnelling on the Great Dyke of Zimbabwe using analytical, empirical, and kinematic methods
- Conference Proceedings
- DOI reference: 10.56952/ARMA-2025-0589
Room and pillar layout analysis for a Great Dyke of Zimbabwe deposit
- Conference Proceedings
- DOI reference: 10.56952/ARMA-2025-0588
A Sustainable and Practical Machine Learning Approach Using Scikit-Learn for Predicting Stope Instability: Identification of Critical Geotechnical Factors
- Journals
- DOI reference: 10.17794/rgn.2025.5.14
An Artificial Intelligence-Based Modification to NHV Estimation of Biomass
- Conference Proceedings
- DOI reference: 10.1007/978-3-031-87558-8_45
A combined application of advanced statistical, soft computing and least square methods for the prediction of higher heating value of coal
- Journals
- DOI reference: 10.1080/19392699.2025.2593959
Real-Time Drilling Control for Hanging-Wall Stability: SCADA-Based Mitigation of Overbreak and Dilution in Long-Hole Stoping
- Journals
- DOI reference: 10.3390/mining5040068
Modernization of Hoisting Operations Through the Design of an Automated Skip Loading System—Enhancing Efficiency and Sustainability
- Journals
- DOI reference: 10.3390/mining5040062
Recent advances in blockchain technology: prospects, applications and constraints in the minerals industry
- Journals
- DOI reference: 10.1080/17480930.2024.2319453
On the impact of Industrial Internet of Things (IIoT) - mining sector perspectives
- Journals
- DOI reference: 10.1080/17480930.2024.2347131
Towards application of positioning systems in the mining industry
- Journals
- DOI reference: 10.1504/IJMME.2024.138723
Predictive modelling for coal abrasive index: Unveiling influential factors through Shallow and Deep Neural Networks
- Journals
- DOI reference: 10.1016/j.fuel.2024.132319
Prioritising the Experimental Procedures for Mode I Fracture Toughness Using Fuzzy Group Multi Criteria Decision Making (MCDM)Â Methods
- Journals
- DOI reference: 10.1007/s00603-024-04123-x
Investigation into the rock mass response to pillar extraction in a hard rock tabular mine
- Conference Proceedings
- DOI reference: 10.56952/ARMA-2024-1011
Geotechnical design for open pit coal mining in proximity to electrical power lines: risks, mitigation, and regulatory compliance
- Conference Proceedings
- DOI reference: 10.56952/ARMA-2024-1003
Comparative investigation of spontaneous combustion of biomass, hydrochar, coal and their blends using Wits-Ehac and thermogravimetric analysis
- Journals
- DOI reference: 10.1080/19392699.2024.2312174
Numerical modeling application in the design of regional pillars for an ore-replacement project: underground platinum mining case study
- Conference Proceedings
- DOI reference: 10.56952/ARMA-2023-0795
Safe mining operations through technological advancement
- Journals
- DOI reference: 10.1016/j.psep.2023.05.052
Enhancement of efficient coal fragmentation through technological advancement
- Journals
- DOI reference: 10.1504/ijmme.2023.131614
Prediction of Thermal Coal Ash Behavior of South African Coals: Comparative Applications of ANN, GPR, and SVR
- Journals
- DOI reference: 10.1007/s11053-023-10192-6
A review of geospatial technology-based applications in mineral exploration
- Journals
- DOI reference: 10.1007/s10708-022-10784-4
Challenges and applications of digital technology in the mineral industry
- Journals
- DOI reference: 10.1016/j.resourpol.2023.103978
Optimization of porous carbons for methane adsorption from South African coal wastes
- Journals
- DOI reference: 10.1080/19392699.2022.2040493
Inhibition of Spontaneous Combustion Characteristic of Biomass Treated with Imidazolium-Based Ionic Liquids Using Thermogravimetric Analysis
- Journals
- DOI reference: 10.1021/acsomega.3c03265
Recycling of Trees Planted for Phytostabilization to Solid Fuel: Parametric Optimization Using the Response Surface Methodology and Genetic Algorithm
- Journals
- DOI reference: 10.1021/acsomega.2c06272
Effects of Proximate Analysis on Coal Ash Fusion Temperatures: An Application of Artificial Neural Network
- Journals
- DOI reference: 10.1021/acsomega.3c04113
A COMPARATIVE STUDY ON POWER CALCULATION METHODS FOR CONVEYOR BELTS IN MINING INDUSTRY
- Journals
- DOI reference: 10.1080/17480930.2021.1949859
Computational intelligence-based models for predicting the spontaneous combustion liability of coal
- Journals
- DOI reference: 10.1080/19392699.2020.1741558
Self-heating characteristics of materials for producing activated carbon
- Journals
- DOI reference: 10.1080/19392699.2020.1729138
Prediction of gross calorific value of solid fuels from their proximate analysis using soft computing and regression analysis
- Journals
- DOI reference: 10.1080/19392699.2019.1695605
On the spontaneous combustion liability of South African coal: a report
- Journals
- DOI reference: 10.1080/19392699.2021.1884554
Overview of mine rescue approaches for underground coal fires: A South African perspective
- Journals
- DOI reference: 10.17159/2411-9717/1738/2022
Application of metaheuristic based artificial neural network and multilinear regression for the prediction of higher heating values of fuels
- Journals
- DOI reference: 10.1080/19392699.2020.1768080
Predicting the peak particle velocity from rock blasting operations using Bayesian approach
- Journals
- DOI reference: 10.1007/s11600-022-00727-5
On the Performance Assessment of ANN and Spotted Hyena Optimized ANN to Predict the Spontaneous Combustion Liability of Coal
- Journals
- DOI reference: 10.1080/00102202.2020.1815196
Prediction of thermal conductivity of granitic rock: an application of arithmetic and salp swarm algorithms optimized ANN
- Journals
- DOI reference: 10.1007/s12145-022-00880-x
The Spontaneous Combustion of Chemically Activated Carbons from South African Coal Waste
- Journals
- DOI reference: 10.1080/00102202.2020.1854747
Predictions of elemental composition of coal and biomass from their proximate analyses using ANFIS, ANN and MLR
- Journals
- DOI reference: 10.1007/s40789-020-00346-9
An Artificial Intelligence-based Model for the Prediction of Spontaneous Combustion Liability of Coal Based on Its Proximate Analysis
- Journals
- DOI reference: 10.1080/00102202.2020.1736577
Spontaneous Combustion Liability Indices of Coal
- Journals
- DOI reference: 10.1080/00102202.2020.1754208
Empirical Estimation of Uniaxial Compressive Strength of Rock: Database of Simple, Multiple, and Artificial Intelligence-Based Regressions
- Journals
- DOI reference: 10.1007/s10706-021-01772-5
On the dependence of predictive models on experimental dataset: a spontaneous combustion studies scenario
- Journals
- DOI reference: 10.1080/17480930.2021.1884336
Prediction of Mechanical Properties of Coal from Non-destructive Properties: A Comparative Application of MARS, ANN, and GA
- Journals
- DOI reference: 10.1007/s11053-021-09955-w
Countermeasures against coal spontaneous combustion: a review
- Journals
- DOI reference: 10.1080/19392699.2021.1920933
A comparative application of the Buckingham ? (pi) theorem, white-box ANN, gene expression programming, and multilinear regression approaches for blast-induced ground vibration prediction
- Journals
- DOI reference: 10.1007/s12517-021-07391-x
On the Application of the Novel Thin Spray-on Liner (TSL): A Progress Report in Mining Operations
- Journals
- DOI reference: 10.1007/s10706-021-01861-5
On the application of drones: a progress report in mining operations
- Journals
- DOI reference: 10.1080/17480930.2020.1804653
Towards an emergency preparedness for self-rescue from underground coal mines
- Journals
- DOI reference: 10.1016/j.psep.2021.03.049
Development of multiple soft computing models for estimating organic and inorganic constituents in coal
- Journals
- DOI reference: 10.1016/j.ijmst.2021.02.003
Determination of semi-mobile in-pit crushing and conveying (SMIPCC) system performance
- Journals
- DOI reference: 10.1007/s12517-021-06550-4
Influence of antioxidants on spontaneous combustion and coal properties
- Journals
- DOI reference: 10.1016/j.psep.2021.02.017
Prediction of rock penetration rate using a novel antlion optimized ANN and statistical modelling
- Journals
- DOI reference: 10.1016/j.jafrearsci.2021.104287
Spontaneous combustion liability between coal seams: A thermogravimetric study
- Journals
- DOI reference: 10.1016/j.ijmst.2020.03.006
Analysis of spontaneous combustion liability indices and coal recording standards/basis
- Journals
- DOI reference: 10.1016/j.ijmst.2020.03.016
A review of research on spontaneous combustion of coal
- Journals
- DOI reference: 10.1016/j.ijmst.2020.03.001
Technology adoption in mining: A multi-criteria method to select emerging technology in surface mines
- Journals
- DOI reference: 10.1016/j.resourpol.2020.101879
The impact of mining on sustainable practices and the traditional culture of developing countries
- Journals
- DOI reference: 10.1007/s13412-020-00613-w
Application of gene expression programming, artificial neural network and multilinear regression in predicting hydrochar physicochemical properties
- Journals
- DOI reference: 10.1186/s40643-020-00350-6
Investigating the effects of gemstone mining on the environs: A case study of Komu in Southwestern Nigeria
- Journals
- DOI reference: 10.1504/IJMME.2020.108640
An overview of conventional and non-conventional techniques for machining of titanium alloys
- Journals
- DOI reference: 10.1051/mfreview/2020029
Performance evaluation of inorganic salts on spontaneous combustion liability
A review of spontaneous combustion studies–South African context
- Journals
- DOI reference: 10.1080/17480930.2018.1466402
Influence of organic and inorganic properties of coal-shale on spontaneous combustion liability
- Journals
- DOI reference: 10.1016/j.ijmst.2019.02.006
Spontaneous combustion liability of coal and coal-shale: a review of prediction methods
- Journals
- DOI reference: 10.1007/s40789-019-0242-9
Prediction of the spontaneous combustion liability of coals and coal shales using statistical analysis
- Journals
- DOI reference: 10.17159/2411-9717/2018/v118n8a2
A new apparatus to establish the spontaneous combustion propensity of coals and coal-shales
- Journals
- DOI reference: 10.1016/j.ijmst.2018.05.012
Spontaneous combustion of coals and coal-shales
- Journals
- DOI reference: 10.1016/j.ijmst.2018.05.013
Comparative analysis of coal and coal-shale intrinsic factors affecting spontaneous combustion
- Journals
- DOI reference: 10.1007/s40789-018-0222-5
Modelling spontaneous combustion liability of carbonaceous materials
- Journals
- DOI reference: 10.1007/s40789-018-0209-2