Saisri Vishwanath

Built an LLM-powered research assistant for easy access to university research documents by combining semantic search (BERT + cosine similarity), RAG architecture (OpenAI + Pinecone), and contextual summarization via prompt engineering, boosting retrieval precision by 30%. Applied NER and sentiment analysis to extract key entities and evaluate user feedback, enhancing contextual relevance and resp

Led the end-to-end migration of employee lifecycle data to Oracle Cloud Infrastructure (OCI), conducting detailed root cause analysis on data discrepancies and implementing validation scripts to ensure 100% data integrity across 1M+ records. Developed 30+ complex SQL analytical reports to support workforce planning and compliance, reducing report execution time by 50%. Reduced data processing time

Improved product image classification accuracy by 15% for an e-commerce vehicle parts platform using transfer learning with VGG and GAN-based data augmentation, enhancing product tagging for accurate search. Built and deployed a demand forecasting model using Random Forest Regressor to predict product-level inventory needs, leveraging feature importance to identify key demand drivers and reducing

Grade: 3.7/4

Activities and societies: Coursework: Statistics, Machine Learning, Natural Language Processing, Reinforcement Learning, Large Language Models, Data Mining and Analytics

Pursued a Master of Science in Computer Science, focusing on advanced topics such as Machine Learning, Natural Language Processing, and Large Language Models. Achieved a GPA of 3.7/4 and was recognized as a Merit Scholar.

Grade: 9/10

Activities and societies: Coursework: Mathematics, Algorithms, Object-Oriented Programming, Operating Systems, Artificial Neural Networks, Deep Learning, Data Science.

Completed a Bachelor of Engineering in Electronics and Communication, with coursework covering Mathematics, Algorithms, and Data Science. Maintained a GPA of 9/10 and was awarded a Merit Scholarship.