Deepam Goyal

Built a continuous authentication system analyzing 25+ behavioral features with 95% accuracy and <1 second ML inference for real-time fraud detection in mobile banking applications.

Developed autoencoder neural networks (32-16-32 architecture) with personalized user models, achieving a 3-5% false positive rate and an adaptive 3-tier risk assessment system.

Created a full-featured Flutter banking app with 8+ services (UPI, transfers, recharge), demonstrating seamless behavioral monitoring integration with an encrypted cloud ML pipeline.

Designed and developed a scalable e-commerce backend with Go, splitting logic into modular microservices for enhanced performance and maintainability.

Implemented a high-performance gRPC communication layer, cutting inter-service latency by 40% across services.

Integrated a GraphQL gateway to enable a unified, flexible API access layer for diverse client applications.

Optimized data workflows using PostgreSQL and Elasticsearch, achieving 300ms average product search time.

Containerized and orchestrated all services via Docker Compose for reproducibility and seamless deployment.

Designed and deployed a full-stack real estate platform serving 500+ listings, improving page load speed by 35% through optimized asset delivery.

Engineered robust RESTful APIs via Express.js and streamlined data access using Prisma ORM for MongoDB.

Implemented advanced search and filtering via React Query, reducing data fetch latency by 60% for improved user experience.

Integrated Auth0 for secure authentication and session handling, enabling robust role-based access control and user management.