Raksha Shet

Objective: Leverage Large Vision-Language Models (LVLMs) to enhance industrial anomaly detection and generate human-friendly descriptions of defects - Conduct an extensive literature review on state-of-the-art anomaly detection methods and LVLM applications -Implement semi-automatic labeling techniques to streamline data annotation. -Fine-tune LVLM modules to improve both detection accuracy and interpretability -Performance evaluation of the fine-tuned LVLM against pre-trained models to assess improvements

-Driving Siemens Industrial Edge AI technologies with Industrial AI Deployment Team to deploy projects, advancing industrial applications -Engage with specialists to design technology solutions and participate in industry events, delivering demos for customer visits and showroom presentations to achieve project objectives

-Facilitated training sessions and crafted coding challenges, ensuring seamless learning while supporting mentor research initiatives -Gained proficiency in ML and AI through theoretical coursework and practical projects

Implemented an IoT-based smart traffic system using RFID technology to prioritize ambulance routes and transmit patient vitals to nearby hospitals in real-time, optimizing emergency response in smart cities