Murali M

About Murali M

Innovative and results-driven Generative AI Engineer with over 8 years of experience in…

Experience

1. Generative Ai Engineer

   Charter Communications

   Feb 2024 — Present

   Developed autonomous AI agents for healthcare data analysis, providing actionable insights to clinical stakeholders •Implemented RAG pipelines to enhance retrieval of medical information for patient support systems •Optimized LLM models for healthcare-specific terminology and compliance requirements •Created personalized patient communication systems using advanced NLP techniques •Designed and deployed medical document summarization tools using GPT models and custom embeddings •Integrated healthcare knowledge bases with vector databases for improved information retrieval •Applied differential privacy techniques to ensure HIPAA compliance in AI model training •Developed anomaly detection systems for identifying unusual patterns in patient data •Built real-time processing pipelines using Kafka and Spark for healthcare analytics •Implemented conversational AI solutions for patient engagement and support •Created dashboards in Google Data Studio and Tableau for visualizing healthcare metrics •Optimized SQL queries and data warehousing solutions to support business intelligence •Enhanced healthcare claims processing using Apache Spark and AWS services •Collaborated with clinical teams to refine model outputs for medical accuracy •Integrated chatbots with electronic health record systems for seamless data access •Deployed machine learning models with high availability for critical healthcare applications •Designed fallback mechanisms for AI systems to ensure patient safety and data integrity •Conducted A/B testing to validate improvements in patient experience and clinical outcomes.•Developed medical Q&A systems using fine-tuned LLMs on curated domain-specific datasets.•Automated the extraction of ICD-10 codes from clinical documentation using advanced NLP pipelines.•Designed knowledge graphs integrating EHR data to improve AI explainability and clinical decision-making.