Prathyusha Nandigam

Developed and maintained CI/CD pipelines using Jenkins, GitHub Actions, Maven, and SonarQube for continuous integration, build automation, static code analysis, and artifact management via Nexus. Provisioned and managed Azure cloud infrastructure including AKS, Virtual Machines, VNets, Storage Accounts, SQL Databases, and Application Insights using Terraform, ARM templates, and Ansible.

Architected and deployed a scalable digital healthcare ecosystem Hospice, utilizing React.js (frontend), Node.js (backend), and MongoDB, achieving a 55% improvement in patient outcomes by addressing healthcare disparities through cloud-hosted infrastructure and modern web technologies. Integrated a comprehensive care model using RESTful APIs and dynamic graph structures, optimizing data flow and r

Developed a one-shot learning model using Siamese Neural Networks with Keras and TensorFlow, achieving 92% accuracy in classifying unseen images with minimal training data; leveraged GenAI for performance interpretation. Designed and trained a CNN-based Siamese architecture using contrastive loss and Adam optimizer, improving model optimization efficiency by 25%.

Built and managed CI/CD pipelines using Jenkins, integrating with GitHub and Subversion, and automating deployments across IFTE, FTE, Pre-prod, and Production environments, enabling over 100 applications to deploy in under 10 minutes. Designed and deployed containerized applications using Docker and Kubernetes across Azure, AWS, and GCP, enhancing scalability, high availability, and infrastructure

Completed a Master's degree focusing on Applied Computing with a specialization in Artificial Intelligence. Gained expertise in deploying predictive analytics and AI-driven healthcare systems through Canadian internship experience.

Obtained a Bachelor of Technology in Computer Science and Engineering. Developed a strong foundation in computer science principles and engineering practices.