CFD & Computational Hemodynamics
Transient flow modelling, hemodynamic metrics, aortic morphology studies, boundary-condition design, verification, and publication-quality interpretation.
CFD • Computational Hemodynamics • Data Analysis • Applied AI
Building serious technical systems from simulation, data, and automation.
I work across cardiovascular CFD, quantitative analysis, and practical AI tooling — turning technically heavy workflows into reproducible pipelines, clear evidence, and usable engineering systems.
CFD
Cardiovascular flow modelling and hemodynamic interpretation
Data
Decision-ready analysis and visual storytelling
AI
Practical automation and engineering tool design
About
Deep technical work, presented with clarity.
My background combines mechanical engineering, cardiovascular CFD, scientific programming, biomedical research, and analytical reporting. I care about two things: technical rigor and practical usefulness.
That means building reproducible workflows, documenting assumptions well, turning raw outputs into interpretable evidence, and designing systems that reduce wasted effort.
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The goal is not just to generate results. The goal is to make complex technical work trustworthy, explainable, and useful to the people making decisions from it.
Core domains
Three areas I am deliberately building around
This structure keeps the portfolio sharp: simulation depth, analytical interpretation, and tool building.
Data Analysis & Machine Learning
Turning complex datasets into structured findings through cleaning, comparison, concentration analysis, visual storytelling, and model-oriented thinking.
Applied AI & Automation
Building tools and workflows that reduce manual effort, improve repeatability, and make technical knowledge easier to access and use.
Selected work
Projects
Organised by domain so the site feels intentional rather than like a random stack of cards.
Category 01
CFD & Computational Hemodynamics
Cardiovascular research
Thoracic Aortic Hemodynamics Studies
Simulation-driven studies of healthy and diseased aortic flow, focusing on wall shear stress, helicity, flow efficiency, morphology effects, and clinically relevant interpretation.
- Transient cardiovascular CFD
- Verification and sensitivity analysis
- Publication-grade figure and result generation
Pipeline design
Automated CFD Workflow
A structured workflow for geometry preparation, meshing, solver setup, and reproducible post-processing for cardiovascular simulation studies.
- Reduces manual setup time
- Improves consistency and traceability
- Supports scale-up for larger parameter studies
Category 02
Data Analysis & Machine Learning
Featured case study
South Australian Housing Stress Analysis
An evidence-led analysis of South Australian housing-stress data designed to show where affordability pressure is concentrated, which income groups are most exposed, and how tenure type shapes the burden. The case study turns a public dataset into a clean, policy-facing story with clear definitions, figure-by-figure interpretation, and portfolio-quality presentation.
Python-based analysis
Comparative visualisation
Concentration analysis
Insight writing
Structured storytelling
Figure slot ready
fig01_top15_lgas_clean.png
Drop the real chart into the housing-stress figures folder and it will appear automatically.
Figure slot ready
fig05_cumulative_share_lgas.png
This preview card becomes the real figure as soon as the PNG exists in the expected folder.
Figure slot ready
fig06_vulnerability_scatter.png
The homepage is already wired to the exact filenames, so no extra editing is needed later.
Category 03
Applied AI & Automation
AI assistant concept
Ansys Fluent Support Assistant
An AI tool designed to explain CFD fundamentals and provide step-by-step task guidance for Fluent users in practical engineering workflows.
- Fundamental explanations for learners
- Task-based guidance for software workflows
- Lower barrier to effective CFD practice
Healthcare tool direction
AI + MRI + Hemodynamic Analysis
A direction focused on combining imaging-derived data, simulation outputs, and intelligent tooling to support clinically useful cardiovascular analysis.
- MRI-informed data workflows
- Engineering interpretation layers
- Future decision-support potential
Workflow automation
Research-to-Report Automation
A broader automation philosophy for turning technical outputs into clean figures, consistent summaries, and decision-ready reporting with less manual repetition.
- Python-driven repeatable reporting
- Cleaner handoff from analysis to communication
- Less friction in technical projects
Professional profile
Curriculum Vitae
A detailed summary of my research, technical experience, publications, awards, and teaching background.
Contact
Let’s build something serious.
Research collaboration, engineering automation, AI tools, data work, or a sharp technical conversation.