At Artemis UAV, I designed and optimized computer vision algorithms for real-time bird detection across environmental conditions and lighting profiles. The system achieved 80% accuracy at 30 FPS for UAV-based wildlife monitoring.
At Devsinc, I contributed to the Turing project by developing mock code and test suites to validate core system functionality. I also used automated testing and edge-case validation to support reliable model deployment.
As an Artificial Intelligence Intern at Zeetech, I contributed to machine learning systems and worked across the ML lifecycle, from data collection and preprocessing through model training, evaluation, and integration.
My projects include a university website chatbot using RAG, a federated learning model for identifying machine-generated text, and a Chrome extension that offers contextual assistance with multiple LLMs. I also developed an autonomous drone-based crop protection system that detects and deters birds in real time.
