Associate Professor · University of Pretoria

Muaaz
Bhamjee

Mechanical & Aeronautical Engineering

Computational Fluid Dynamics Granular Dynamics Lattice Boltzmann Method Scientific Machine Learning AI & Climate Intelligence High-Energy Physics ATLAS / CERN Quantum Computing Quantum Sensing
63h-index (Scholar)
31h-index (Scopus)
200+Publications
9Masters Supervised
3Masters Supervising
7Doctorates Supervising
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From turbulent flows
to colliding protons

I am an Associate Professor in the Department of Mechanical & Aeronautical Engineering at the University of Pretoria, leading research that spans the full spectrum of computational and theoretical physics — from the macroscale dynamics of granular and multiphase flows to the subatomic world of high-energy particle collisions at CERN.

My research lab — the CERG-FLUX Lab (Fluids, Learning, and Uncertainty in compleX systems) — is a subgroup within the Clean Energy Research Group (CERG) at UP. We develop and apply the Lattice Boltzmann Method (LBM) and Euler–Euler CFD frameworks on HPC infrastructure, resolving multiphase flow in industrial process equipment including hydrocyclones, fluidised beds, and biomedical devices. This computational mechanics foundation connects naturally to my work on scientific machine learning — physics-informed neural networks for Navier–Stokes problems — and to AI-based climate intelligence, where I co-developed the open-source Granite Geospatial Land Surface Temperature Earth Observation Foundation Model at IBM Research Africa.

At the frontier of fundamental physics, I am a contributing author on the ATLAS Collaboration at CERN, with publications spanning Higgs boson characterisation, top quark physics, and the landmark 2024 Nature observation of quantum entanglement with top quarks. New programmes in quantum computing, quantum machine learning, and quantum sensing — pursued through the University of Pretoria Quantum Science and Technology group (UPQuST) — extend this quantum thread into engineering applications.

I am Vice-President of the Executive Committee of the South African Association for Theoretical and Applied Mechanics (SAAM) and Vice-President of the South African National IUTAM Committee.

Current Position
Associate Professor
Mechanical & Aeronautical Engineering
University of Pretoria

Areas of investigation

Principal Investigator of the CERG-FLUX Lab, coordinating six interlocking research programmes spanning four orders of magnitude in physical scale.

CERG-FLUX Lab — Fluids, Learning, and Uncertainty in compleX systems

A research subgroup within the Clean Energy Research Group (CERG) at the University of Pretoria. CERG-FLUX develops physics-informed computational methods to understand transport phenomena — spanning computational fluid dynamics and multiphase flow, lattice Boltzmann methods, scientific machine learning, high-energy particle physics at CERN, and quantum technologies.

cerg-flux-lab.github.io · GitHub

🌀

Computational Fluid Dynamics & Granular Flow

Multiphase and granular flow modelling in process equipment — hydrocyclones, fluidised beds, pneumatic conveyors — using Lattice Boltzmann Method (LBM) and Euler–Euler frameworks. Flow regimes span laminar, turbulent, and dense granular packing. Industrial partner: Multotec Pty. Ltd.

LBMMultiphase FlowGranular DynamicsHydrocyclonesHPCOpenFOAM
⚛️

High-Energy Physics — ATLAS at CERN

Contributing author on the ATLAS Collaboration at CERN. Research includes detector environmental monitoring for the ITk upgrade, Higgs boson characterisation, top quark physics, and the landmark Nature 2024 observation of quantum entanglement with top quarks.

ATLASHiggs BosonTop QuarksHL-LHCITk Upgrade
🌍

Scientific Machine Learning & Climate AI

Physics-informed neural networks (PINNs) and neural operators for forward and inverse problems in fluid dynamics — embedding conservation laws as inductive bias. Active work on Navier–Stokes PINNs with explicit boundary-condition enforcement and Reynolds-number generalisability. Extends to foundation model development for geospatial Earth observation, including the open-source Granite Geospatial Land Surface Temperature model co-developed at IBM Research Africa, and urban heat island characterisation using vision transformers.

PINNsNeural OperatorsPyTorchFoundation ModelsPrithvi / ViTUrban Heat IslandsGeospatial AI
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Quantum Technologies

Quantum computing, quantum machine learning, and quantum sensing for engineering applications, pursued through the University of Pretoria Quantum Science and Technology group (UPQuST) — UP's node in the South African Quantum Technology Initiative (SA QuTI). Builds on connections between ML pipelines in particle physics and emerging quantum architectures, with dedicated funding and industry partnerships.

UPQuSTSA QuTIQuantum ComputingQuantum Machine LearningQuantum Sensing
🏥

Biomedical & Health CFD

CFD modelling of respiratory droplet transmission and UV germicidal irradiation for infection control, ventriculoperitoneal shunt dynamics, and lung acoustics. Collaboration with the Perinatal HIV Research Unit (PHRU) at Wits.

Droplet DynamicsUVGIVP ShuntsBiomedical Flow
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Engineering Education

Scholarship of teaching and learning with a focus on design literacy, academic voice, blended and online learning, and decolonisation of engineering curricula in post-Apartheid South Africa.

Design LiteracyBlended LearningDecolonisationSASEE

Selected outputs

A selection of recent and high-impact publications. Full list on Google Scholar and Scopus.

2024
Observation of quantum entanglement with top quarks at the ATLAS detector
Nature, vol. 633, pp. 542–547
Nature / ATLAS
2025
Characterising the Higgs boson with ATLAS data from the LHC Run-2
Physics Reports, vol. 1116, pp. 4–56
ATLAS
2025
Auxiliary Feature Injection for Prithvi-ViT Fine-Tuning on Geospatial Data
IEEE IGARSS 2025, Brisbane, pp. 1075–1078
AI / Geo
2025
Reservoir Computing for Predicting Chaotic Dynamical Systems
69th Annual Conference of the South African Institute of Physics (SAIP 2025), pp. 1026–1031
AI / Physics
2024
Detection and Characterization of Urban Heat Islands with Machine Learning
IGARSS 2024 – IEEE International Geoscience and Remote Sensing Symposium, Athens, pp. 1693–1699
AI / Geo
2024
Infectiousness model of expelled droplets exposed to ultraviolet germicidal irradiation
Computers & Fluids, vol. 275, p. 106242
CFD
2022
The Modification of the Dynamic Behaviour of Cyclonic Flow in a Hydrocyclone under Surging Conditions
Mathematical and Computational Applications, vol. 27(6), p. 88
CFD / Granular
2021
Modelling of a Heated Gas-solid Fluidised Bed using Eulerian Based Models
R&D Journal of the South African Institution of Mechanical Engineering, vol. 37, pp. 45–57
CFD / Granular
2020
Experimental and CFD Investigation of a Hybrid Solar Air Heater
Solar Energy, vol. 195, pp. 413–428
CFD
2013
An Experimentally Validated Mathematical and CFD Model of a Supply Air Window: Forced and Natural Flow
Energy and Buildings, vol. 57, pp. 289–301
CFD

Academic & industry positions

2025 — Present
Associate Professor
Department of Mechanical & Aeronautical Engineering, University of Pretoria
Leading research programmes in computational mechanics, quantum computing & sensing, and AI. Supervision of postgraduate students and development of new quantum science curricula.
2021 — 2025
Staff Research Scientist
IBM Research Africa, Johannesburg
Led the Urban Heat Island AI programme. Co-developed the open-source Granite Geospatial Land Surface Temperature foundation model. Patent holder for dynamically forecasting high-resolution air temperature (ZA2023/09448).
2021 — 2025
Visiting Senior Research Associate
University of Johannesburg
Continued postgraduate supervision and ATLAS / SA-CERN activities alongside IBM Research role.
2017 — 2021
Senior Lecturer
Department of Mechanical Engineering Science, University of Johannesburg
Course coordinator for Introduction to Engineering Design 1A & 1B. Principal Investigator on two funded research projects. Completed DIng (Computational Fluid & Granular Dynamics).
2008 — 2009
Junior CFD Analyst
Hatch Africa — Specialised Engineering Analysis & Design (SEAD) Group
Industry foundation in computational mechanics applied to large-scale engineering consulting projects.

Get in touch

Open to research collaborations, postgraduate enquiries, and speaking invitations.