Computational Biology
Multi-omics integration, bulk and single-cell transcriptomics, and structural modelling, with a focus on oncogenomics and precision medicine.
Open group →One question — how disease arises, spreads and is best treated in Bangladesh — approached at four scales. Each group owns a scale; projects usually cross two or more.
Multi-omics integration, bulk and single-cell transcriptomics, and structural modelling, with a focus on oncogenomics and precision medicine.
Open group →Epidemiological surveillance, national survey analytics, digital health evaluation and evidence synthesis for health policy.
Open group →Clinical risk prediction, biomedical image analysis, interpretable models and biomarker discovery pipelines.
Open group →Spatial epidemiology, earth observation, healthcare accessibility modelling and environmental health risk mapping.
Open group →Every project follows the same route, because the route is the thing we are teaching. Students join at step one, not at the analysis.
Literature review, a written hypothesis, and a pre-specified analysis plan before any data is touched.
Reproducible pipelines in R or Python, version-controlled in the open from the first commit.
Weekly review with a supervisor, adversarial reading of the result, and figures built to be understood.
Manuscript drafting, submission and revision, with the student as first author.
We take on collaborations with laboratories, hospitals, universities and non-profits — usually contributing computational analysis to a study that already has the domain expertise and the data.