Services

I am open to selected collaborations and consulting work at the intersection of biomedical data, interpretable machine learning, retinal imaging, and mathematical modelling.

This page is intended as a clear entry point for research groups, academic collaborators, clinicians, startups, and technical teams who may want support on scientifically rigorous data-driven projects.

Areas I Can Help With

• Biomedical data analysis for multimodal datasets involving imaging, clinical variables, omics, or genetics
• Interpretable machine learning workflows where explanation and model transparency matter
• Statistical modelling including regression, multivariate methods, mediation, and causal analysis
• Retinal imaging and oculomics projects involving feature extraction, biological interpretation, or downstream modelling
• Scientific computing and research pipelines for reproducible analysis, benchmarking, and result reporting
• Research writing and technical review for methods sections, mathematical explanations, and analytical framing

Typical Collaboration Formats

• Short technical consultation
• Research collaboration
• Analytical support for a specific dataset
• Method development for an ongoing scientific project
• Independent review of modelling strategy or analytical design
• Scientific content or technical article development

What I Prioritise

I am especially interested in work that values:

• interpretability over black-box claims
• methodological clarity
• strong quantitative reasoning
• reproducible workflows
• biomedical relevance

Good Fit Projects

Examples of projects that are likely to be a good fit:

• retinal imaging linked with systemic or molecular traits
• multimodal biomedical integration
• causal or mediation-oriented analysis
• mathematically grounded machine learning for healthcare
• signal, wave, or geometry-based scientific modelling

Contact

If you would like to discuss a project, collaboration, or consulting request, the simplest route is to contact me directly:

• Email: i1n23@soton.ac.uk
• LinkedIn: Inam Ullah Khan
• Website: inamullah-colab.github.io

When reaching out, it helps if you include:

• a short description of the problem
• the type of data involved
• the goal of the work
• whether the request is academic, collaborative, or paid consulting