My Projects
Crop Disease Detection
Ensemble AI Models for Mobile Agriculture
Built ensemble models combining VGG16, InceptionV3, MobileNetV2, and custom CNNs to detect crop diseases. Trained on 60,000+ plant images covering 40+ disease
types, achieving ~99% accuracy with mobile optimization for smallholder farmers. (Accepted to IEEE ICIH 2025)
Code-Mixed NLP (Awarded CREST Gold)
English-Telugu Text Processing
Designed Natural Language Processing systems for English-Telugu code-mixed text processing utilizing Perceptron Classifiers, Hidden Markov Models, and Recurrent Neural Networks. Focused on making AI language-inclusive for diverse communities.
AgroLend Platform
AI-Powered Financial Literacy for Farmers
Developed an AI chatbot that speaks to South Indian farmers in their native languages, helping them understand financial schemes, loans, and insurance. Features AI-gen video content for easy comprehension with content verified by State Bank of India.
VIVA MUN Leadership
Largest MUN in Andhra Pradesh
Led 19-member team organizing largest MUN in Andhra Pradesh with 500+ delegates. Secured nearly $6000 in sponsorship funding, built conference website, implemented SEO techniques, and developed automation scripts for operations.
Crop Health Assessment
AI-Powered Pest & Deficiency Detection
Developed dual-function computer vision system combining nutrient deficiency detection and pest identification using CNNs. Achieved over 90% accuracy in detecting nitrogen, phosphorus, potassium deficiencies. Created mobile-optimized deployment for smallholder farmers to reduce fertilizer costs.
Purpose Academy
UC Berkeley Entrepreneurship Program
Selected among 25 students from India for prestigious entrepreneurship program at UC Berkeley’s Sutardja Center for Entrepreneurship & Technology. Participated in
week-long immersion learning Berkeley Method of Entrepreneurship, visited tech companies
(Intel, Uber, NVIDIA).
AI/ML Specialization Certification
Stanford ML Specialization + Advanced Placement
Completed Stanford University’s Machine Learning Specialization with 99.92% final grade. Covered supervised learning, unsupervised learning, reinforcement learning, and neural networks. Gained expertise in TensorFlow, Keras, and scikit-learn libraries.