Riya Garg

Enhanced ECG interpretation efficiency (SaaS) by 40% by building responsive design through web application development as per user requirements and UI design with React, integrating real-time prediction heat-maps and visualizations via Chart.js, and results from predictive models using component libraries, react webpack and Redux while working on both commercial and experimental design as a part of software development life cycle.
Reduced patient-history review time by 20x by engineering a note-organisation UI that clusters clinician notes by guideline relevance for a top-5 pharmaceutical partner, enhancing service delivery.
Achieved a 90% reduction in AI prediction latency (from 30 seconds to under 3 seconds) by optimizing data streaming with EventSource and WebSockets, leveraging critical thinking to meet specification.
Achieved a 10x increase in throughput under HIPAA compliance through detail-oriented service-worker logging and caching strategies during Epic EHR integration, enhancing system observability and applying root cause analysis for improved troubleshooting.
Cut onboarding duration from 1 day to 1 hour for five hospital sites by implementing an end-to-end Docker-Kubernetes containerization solution featuring HAProxy/Nginx (load balancing tools) ingress and continuous integration through Jenkins.
Elevated team efficiency and product quality by applying test-driven development techniques and mentoring interns, cultivating a collaborative environment and leveraging infrastructure management best practices to respond to evolving customer needs.
Improved project organization and verbal and written communication skills by using Jira for project management and Confluence for documentation, enhancing technical support and ensuring all team members were aligned on project goals, contributing to effective metadata management.

Reduced clinical triage time by 90% in the development of a sarcoma clinical decision-support tool by designing and implementing a React-based survey application, leveraging data modeling to optimize question flow and response evaluation.
Accelerated user interface iteration cycles by 50% by translating stakeholder insights into Figma prototypes, utilizing Agile methodologies to rapidly refine front-end user interface designs.
Developed a front-end application that integrates machine learning principles and implements UI/UX design for improved clinical decision-making.

Developing Unity demos for AI-powered SDKs, including Face Tracking, Emotion Detection, AR Filters, Background Removal, Hair Segmentation, and Face Identification.

Writing scripts in C# and Objective-C to integrate neural network outputs into interactive applications.

Deploying and web-hosting Unity demos for cross-platform accessibility.