BHARATH SRI VARDHAN VELDI

Engineered robust Web Events, Web Hooks, Java Spring Boot APIs incorporating pagination, rate limiting and Redis caching, resulting in reduced server latency by 200ms under peak load conditions in production. Translated Figma designs into Angular APIs on a new project, reducing front-end delivery time by 2 weeks and improving key production metrics. Ensured high-quality code by using SonarQube and Veracode for Application testing, resolving 70+ issues related to code smells, by implementing TDD practices with JUnit, Mockito and Rest Assured boosting code coverage by 54%. Enabled faster delivery of revenue-generating features by 30% while reducing production defects by 25% through robust CI/CD pipelines and automated code quality checks. Deployed containerized applications using AWS ECR, ECS, and EKS with Application Load Balancers, cutting deployment time by 4hours per release and improving system uptime by 15%.

Reduced fMRI processing time by 53% by optimizing distributed Multi-GLM models with AI model selection on IUʼs BIGRED200. Improved brain mapping accuracy by 20% through slice timing and field map corrections, preparing outputs for AI functional analysis. Accelerated statistical modeling by 20% by applying linear and nonlinear optimizations, enabling faster parameter estimation. Collaborated with neuroscientists and HPC engineers to integrate AI analysis into high-throughput neuroimaging research workflows.

Developed and deployed 20+ asynchronous APIs for cognitive load experiments using microservices architecture, increasing data accuracy by 15% and enabling seamless integration with AI pipelines using HuggingFace models and ML-ready data formats. Improved system performance by reducing query latency from 800ms to 150ms and page load times from 8s to under 2s by optimizing backend workflows, introducing intelligent caching, and structuring datasets for downstream model training. Automated model deployment and API releases by designing a Docker–Kubernetes CI/CD pipeline, reducing dev effort by 10+ hours/month and supporting future LLM fine-tuning and behavioral tagging automation.

Initiated the implementation of a comprehensive logging infrastructure using Java, React, Spring Boot and microservices; secured log retrieval acceleration from 3 minutes down to just 10 seconds. Orchestrated seamless integration of AWS ElastiCache (Redis) within existing infrastructure for faster log processing capabilities; gained annual cost savings exceeding $100K through strategic resource allocation. Spearheaded enhancements to database performance using read replicas in Amazon RDS while optimizing log searches with complex SQL queries and triggers; achieved a substantial drop of query latency close to 40%. Conducted thorough test-case scenarios with tools like Jest and Mocha to achieve a remarkable 98% code coverage; led to a sharp decrease in bug occurrences during product deployment stages.

Led initiatives aimed at a major service upgrade in the SCOT space by designing Java Spring Boot APIs, enabling annual processing of over 100,000 invoices and enhancing transaction handling capacity for 50K+ operations. Streamlined the processing of more than 200K complex invoices valued at EUR 498K through AWS Step Functions, drastically improving transaction reconciliation accuracy while saving around 40 hours in manual tasks each month. Managed the migration of 70+ environments from MAWS to NAWS, achieving a cost reduction of $322K per year while enhancing system scalability for high-demand events like Prime Day and Q4 peaks.

Taught full-stack development as a web development instructor, empowering students to build and deploy robust applications, to over 100+ students as part of ACM Student chapter. Mentored students in full-stack development, facilitating hands-on experience and practical skills, which significantly boosted their career readiness and technical proficiency.

- As a machine learning instructor at ACM, I played a key role in fostering collaboration and technology awareness in a global community of 100,000 members. - Beyond traditional coding mentorship, I delved into intricate machine learning and deep learning concepts within the tech community. - My instructional experience at ACM included a comprehensive teaching approach covering machine learning and deep learning algorithms.

🚀 Skilled in Data Structures and Algorithms, Software Engineering, Full Stack Development, AWS, React.js, Advanced Database Concepts, Computer Networking, Machine Learning, Deep Learning, Generative AI.