Built and deployed an MCP-based AI assistant using Flowise + AWS Bedrock to automate internal catalog classification, reducing manual lookup time by 70%

Designed end-to-end LLM pipeline (retrieval + orchestration + API integration) used by 500+ daily internal users

Led development from prototype → production deployment, enabling faster onboarding workflows across teams

Applied prior knowledge in AI and machine learning to develop innovative solutions for advanced driver-assistance systems (ADAS). Conducted research on enhancing sensor integration and real-time decision-making algorithms, contributing to the improvement of safety and performance in driver-assistance features

Focused on optimizing cloud-based enterprise applications by leveraging data-driven insights. Analyzed large datasets and proposed innovative solutions to enhance system scalability and efficiency

Raised awareness on the bioethics of animal testing through webinars and articles and Educated the community on cruelty-free product purchasing.