Sandhya Meti

Engineered and implemented a machine learning model to predict waterborne diseases, enhancing public health management through proactive detection and analysis.

• Built a robust machine learning model to accurately predict waterborne diseases and identify effective treatment methods.
• Implemented comprehensive data visualization techniques using Matplotlib, Seaborn, and Folium to facilitate in-depth outbreak analysis.
• Contributed to improved public health management by enabling early disease detection and supporting proactive intervention strategies.

Led the development of a Convolutional Neural Network (CNN) model for accurate pneumonia detection from chest X-ray images, significantly enhancing diagnostic capabilities.

• Developed a CNN model to accurately classify chest X-ray images into normal and pneumonia categories, achieving high precision in medical diagnostics.
• Utilized ResNet50 as a powerful feature extractor, significantly improving the model's detection accuracy and efficiency for image analysis.
• Optimized the classification model through systematic hyperparameter tuning, enhancing overall performance for reliable healthcare diagnostics.

Served as Class Coordinator, fostering a collaborative academic environment and representing student needs within the institution.

• Coordinated academic activities and served as a primary liaison for over 50 students, enhancing communication and support within the class.
• Maintained consistent strong academic performance, setting a positive example for peers and contributing to overall class success.
• Actively participated in multiple college-level coding challenges and hackathons, applying problem-solving skills in competitive environments.
• Demonstrated strong teamwork and adaptability in academic projects, ensuring successful collaboration and project completion.