Raja Kushwah

Responsible for leading and maintaining the GraphDatabaseManager microservice, overseeing its continuous enhancement and ensuring its optimal performance

• Implemented comprehensive object relationship check support for diverse objects and policies in a firewall using Graphdatabase
• Successfully transitioned SaaS-based AWS Neptune graph database to a MongoDB solution, utilizing MongoDB's graphLookup feature
• This strategic move has substantially increased performance and delivered notable cost reductions for company
• Implemented strategic optimizations to significantly enhance the performance of the graph database manager
• Took ownership of developing an automation script in Python to execute CRUD operations on an API, enabling the evaluation of performance for graph database manager microservice

• Successfully integrated multiple Electronic Health Record (EHR) systems such as EPIC, Cerner, Athena Health, and others with third-party applications, ensuring seamless data interoperability and streamlined workflows for enhanced patient care
• Led the development of robust data ingestion processes to efficiently load periodic bulk data from Electronic Health Records (EHRs) into the Graph Database, enabling seamless data integration and providing a foundation for advanced analytics and insights in healthcare operations
• Responsible for design, development, and successful implementation of a Population Health Management (PHM) Dashboard utilizing NeoDash, providing actionable insights of connected data and visualizations to drive informed decision-making for healthcare initiatives.

• Development of a FHIR-based API for exchanging electronic health records, demonstrating expertise in HL7 FHIR
• Implemented US Core Profiles Validator and FHIR Transformer to enable seamless data transformation between FHIR STU3 and FHIR R4 formats
• Analyzing, validating and summarizing data (Electronic Health Record) as per the FHIR standards
• Engineered a Kibana Dashboard to visualize FHIR server logs, providing valuable insights for monitoring and optimization
• Automated healthcare data ingestion through the design and implementation of Python scripts, streamlining data processing and enhancing efficiency.