Research
Research positions
Research Intern
Collects freshly excised endometriotic lesions in the operating room and characterises tertiary lymphoid structures by multiplex immunofluorescence and spatial quantification. Separately built a patient-aware framework integrating RNA-seq with MRI-registered 3D biopsy coordinates, applied to 130 biopsies from 12 glioma patients.
AI in Radiation Oncology Lab
Developed GenoRefine, a deep-learning framework for single-cell RNA-seq integration, benchmarked across three multi-study datasets. Built a pan-cancer pipeline mapping immune-dysregulated ecosystems and immunotherapy-resistance mechanisms.
R&D Intern, two placements
Analysed sickle-cell trial data and built Python neural networks plus a Neo4j knowledge graph linking dosing, labs and comorbidities to vaso-occlusive crises and mortality-related variables. In 2026, supported study design for a breast-cancer medication — both sides of therapeutic development.
Research Intern
Investigated how ZAP-70 mutations affect CAR-T cytokine production and cytotoxicity, with implications for solid-tumour therapies.
Undergraduate Researcher
Developed an AI approach to predict breast-cancer recurrence (IEEE CBMS 2023) and a random-forest model to classify triple-negative breast-cancer subtypes.
Algorithm to bedside
The work spans AI and algorithm development, multi-omics and single-cell integration, wet-lab cancer immunology, patient-derived tissue and spatial analysis, and clinical-trial analytics and prospective study design.
Publications & code
Selected work
Five scholarly works, four of them first-authored — one published, one accepted, two under review.
Deep learning-based multi-omics predictor for breast cancer recurrence
Rahman A, Zhang Y, Park JG · IEEE CBMS, 2023 · published. DOI: 10.1109/CBMS58004.2023.00343
Uncovering immune-dysregulated ecosystems across cancers: a framework for drug discovery to overcome immunotherapy resistance
Rahman A, Mostafa S, Xing L, Islam T · IEEE CBMS, 2026 · accepted.
GenoRefine: a metric-guided geometric refinement framework for integrated single-cell RNA-seq embeddings
Rahman A, Mostafa S, Xing L, Islam T · IEEE Journal of Biomedical and Health Informatics · under review, 2026. Benchmarked across three multi-study datasets.
Neuroimmune interactions in endometriosis pain
Rahman A, Khazaie K, et al. · American Journal of Obstetrics and Gynecology · under review, 2026. An independent hypothesis linking lesion immune suppression, immune–sensory nerve signalling and neural sensitisation to persistent pain.
Shift work migraine disorder: a chronobiology-based meta-analysis
Woldeamanuel YW, Rahman A, et al. · Frontiers in Neurology, 2025 · published, peer-reviewed.
130 biopsies, 12 patients
Longitudinal glioma analysis separating true temporal evolution from regional heterogeneity. Preliminary analysis found greater across-surgery divergence in 10 of 12 patients (83.3%).
3 multi-study datasets
GenoRefine benchmarked across three independent single-cell datasets, built to integrate heterogeneous data without erasing biological signal.
2 AACR meetings
Endometriosis immune architecture (AACR IO 2025) and endometriosis as a neuroimmune disorder (AACR IO 2026), plus cancer-equity work at the Arizona Health Equity Conference.