Research Interests
I am preparing for graduate research at the intersection of applied machine learning, computer vision, health informatics, and AI systems for education. I am especially interested in building models and tools that are evaluated carefully, communicate uncertainty clearly, and can be used responsibly in real-world contexts.
An Ensemble Learning Framework for Neonatal Asphyxia Prediction Using Perinatal Features
Focus: developing a machine learning framework for neonatal risk prediction using perinatal features, with attention to cross-validation, feature reliability, metric stability, and overfitting control.
IoT-Enabled UAV Prototype for Zone-Level Detection and Automated Targeted Spraying of Cotton Leaf Curl Disease
Agronomy Journal
Focus: proposes a low-cost IoT-enabled prototype that integrates UAV-based imaging,disease classification and arduio based acutation for zone level detection & targeted spraying
Research Preparation
- Experience building AI systems from data flow to user-facing interface.
- Interest in reproducible evaluation, clinical relevance, and responsible deployment.
- Comfort reading technical literature and converting ideas into working prototypes.