Sameeksha S Bhat

2nd-year AI & Data Science student at NMIT Bengaluru, specializing in machine learning, computer vision, and real-world ML deployment. I develop end-to-end ML systems — translating models into production-ready applications: 🔹 Real-Time Visitor Counter (YOLOv8, Python): Multi-object tracking on live video streams using centroid-based tracking, deployed via Flask REST API with real-time inference 🔹 Medical Cost Prediction System (Scikit-learn): End-to-end pipeline with feature engineering, model evaluation, and deployment as an interactive Streamlit application 🔹 Pore Pressure Estimation Model (XGBoost, Random Forest): Trained on 11,494 well-log data points, achieving R² = 0.95 using cross-validation and hyperparameter tuning My work spans model development, evaluation, and deployment — covering data preprocessing, feature engineering, and production-level ML systems. Currently exploring: Machine learning in depth Scalable computer vision systems ML model optimization and deployment NLP and bias analysis in AI systems 📄 Research: TechRxiv preprint analyzing bias in GitHub Copilot's multilingual code generation (in progress for journal submission) 🏆 Achievements: Hackathon Winner (Data Analytics) | LIC Merit Scholar | Deloitte Data Analytics Simulation | CGPA: 9.40 Open to Summer 2026 internships in Machine Learning, Data Science, and Computer Vision. 🔗 GitHub: github.com/Sameeksha-S-Bhat 📂 Featured: Visitor Counter | Medical Cost App | Pore Pressure Model Let's connect if you're working on machine learning, computer vision, or applied AI research!