RESEARCH

Experimental systems for multimodal learning, biomedical language models, explainability, and evidence-driven evaluation.

Research evidence

(06) ITEMS
[01]

C-MAT: Cross-Modal Aligned Transformer

A dual-stream transformer for neurodegenerative disease assessment that aligns MRI and resting-state EEG representations while remaining usable when a clinical modality is missing.

Status · Completed

PythonPyTorchTransformers
2026
[02]

BioAlign-QLoRA: Biomedical Knowledge Graph Alignment

Curated 68,444+ gene-disease relationships and adapted Llama-, Mistral-, and Phi-style models with QLoRA to study changes in biomedical embedding alignment.

Status · Completed research project

PythonPyTorchQLoRA
2025
[03]

Exoplanet Habitability Classification & Analysis

Comprehensive ML pipeline analyzing 5,600+ exoplanets from the PHL Exoplanet Catalog to predict habitability. Implemented multiple classification algorithms with model explainability using LIME to interpret planetary characteristics influencing habitability predictions.

PythonScikit-learnPandas
2023
[04]

Gamified Mobile Banking: User Adoption Research

Research study investigating the impact of gamified features on mobile banking app adoption and user engagement among university students in Bangladesh. Comprehensive statistical analysis of 49 respondents with all four hypotheses achieving statistical significance (p < 0.05).

PythonStatistical AnalysisSurvey Research
2023
[05]

Song Virality Prediction Using ML

Predictive model analyzing 114,002 Spotify tracks to forecast song virality. Used clustering-based virality definition with K-Means and multiple classification algorithms achieving 100% accuracy with regularized models.

PythonScikit-learnK-Means
2023
[06]

Enhancing Recession Prediction with XAI

Developed a stacking ensemble model that achieved 96% accuracy and 100% recall in forecasting U.S. recessions. Used SHAP to interpret the model and validate its economic logic.

PythonScikit-learnXGBoost
2024