
An explainable SDN research prototype combining congestion-risk forecasting, policy-aware routing and reproducible Mininet experiments.
HEALTH INFORMATICS · INTELLIGENT SYSTEMS · BACKEND ENGINEERING
I’m Fateha Hossain, a final-year CSE student and Research Assistant working in health informatics, explainable machine learning and backend engineering.

Medical imaging and clinical-data research
Explainability and reproducible evaluation
APIs, data pipelines and deployed applications

An explainable SDN research prototype combining congestion-risk forecasting, policy-aware routing and reproducible Mininet experiments.

A GPU-cluster monitoring prototype combining simulated telemetry, explainable risk scoring and operational alerts.
Ongoing research evaluating parameter-efficient adaptation of vision foundation models (DINOv2, BiomedCLIP, MedSAM) for medical-image classification across DentIRO radiograph datasets.
My current work focuses on trustworthy medical AI, particularly parameter-efficient vision models and explainable analysis of panoramic radiographs. My earlier research includes low-resource Bangla NLP.
Pediatric morphology alignment module for explainable, uncertainty-aware multi-disease detection in panoramic radiographs.
Parameter-efficient adaptation (LoRA, BitFit, VPT) of Vision Foundation Models for dental radiograph classification.
Benchmarked and explainable machine learning approach to tri-class hematological classification for compensated microcytosis.
Health Informatics Research Lab
Contributing to healthcare-oriented machine-learning experiments, reproducible evaluation, and research manuscript preparation.
CSE-Tech
Developing backend features and database-backed APIs across Spring Boot, Laravel, and FastAPI applications.
I’m open to research collaboration, graduate-study opportunities, and conversations about health informatics, explainable machine learning, and backend software engineering.
Dhaka, Bangladesh · Available by email and LinkedIn