Harshitha Chippalaturthy

Video Transcription Summary, Nov 23 - Feb 24

• Developed a robust video content summarization system leveraging advanced prompt engineering to extract key information, generate concise summaries, and enable interactive Q&A.
• Optimized LLM performance through iterative prompt refinement, achieving a 92% summarization accuracy while reducing content analysis time by 40%.
• Enhanced user engagement and data accessibility by transforming unstructured video content into searchable, structured summaries with interactive features.

Personalized Movie Recommendation System , Jul 23 - Oct 23

• Deployed user interactive and personalized movie recommendation system leveraging LLM technology and user demographics.
• Employed advanced prompt engineering to refine LLM outputs, enhancing recommendation accuracy and user satisfaction.
• Delivered highly personalized suggestions through the integration of semantic search and recommendation algorithms.
• Achieved top 9th position in Google Hackathon 23.