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AI-generated image detection system built with EfficientNet, achieving 96.2% accuracy and 95.8% F1-score across modern generative image architectures.
Improved generalization through augmentation and regularization, with a FastAPI inference service and Grad-CAM explainability under <100 ms latency.
Dual-task ML pipeline predicting GitHub issue severity and resolution time, achieving a 91.3% F1-score and 1.8-day RMSE.
Improved prediction performance by 12% through NLP-based feature engineering and model optimization, with FastAPI and automated GitHub API integration.
Nutrition recommendation and calorie prediction system trained on 500+ dietary records, achieving 78% prediction accuracy.
Reduced calorie prediction error by 15% through feature engineering and regression optimization, integrated into a full-stack React and Flask application.
Autonomous oil well choke control system built for the Honeywell Industrial AI Hackathon using a data-driven Digital Twin and Model Predictive Control.
Developed a predictive well model and closed-loop MPC controller to track production targets while maintaining pressure and operational constraints.