Skin Disease Classification
6-class skin disease classifier on 26,632 images using EfficientNet-B0. Achieved 88.61% test accuracy & 0.886 weighted F1-score. Handled 3.91x class imbalance via inverse-frequency weighted loss.
Software Developer |
Experienced programmer with 2+ years of dedicated practice. Recognized for adept problem-solving abilities and a passion for tackling complex challenges. Passionate about building scalable tech solutions with AI, Web Development, and clean code.
B.Tech CSE at SRM University-AP
2023 - 2027
GPA: 8.39/10Minor: E-Commerce
2+ years of dedicated practice tackling complex coding challenges
Building real-world AI applications with modern technologies
6-class skin disease classifier on 26,632 images using EfficientNet-B0. Achieved 88.61% test accuracy & 0.886 weighted F1-score. Handled 3.91x class imbalance via inverse-frequency weighted loss.
AI-powered educational platform with Flask, PostgreSQL, Bootstrap & Gemini AI. Features: authentication, tutor discovery, session booking, step-by-step explanations, quiz creation, and study notes generation.
Full-stack Flask platform with secure authentication, PDF parsing via Google Gemini AI, and LaTeX-powered PDF generation. Enables users to create ATS-friendly resumes with real-time preview.
ML-powered Streamlit app for predicting energy consumption patterns using XGBoost regression with data visualization.
C++ application with distance-based fare calculation, Maps API integration, admin/user roles and file-based data storage.
ML-powered skin health prediction app using XGBoost and explainable AI for early disease detection.
AI-Powered Leaf Disease Detection
SRM University-AP
Always excited to collaborate on projects or new opportunities!