Vedant Patel

Background

About Vedant Patel

I’m a Computer Science senior at UC Davis with deep expertise in building scalable, cloud-native AI systems. As a Software Engineering Intern, I’ve architected containerized, load-balanced pipelines using RAG-based LLMs on Azure/AWS. In my UC Davis research role, I led TinyML and Health-LLM initiatives—delivering a quantized ECG anomaly detector ISCAS accepted) and a personalized Health LLM via fault-tolerant, event-driven data pipelines. Key Expertise & Technologies Cloud & Infrastructure: AWS (EC2, S3, Lambda, ECS/EKS), Azure (VMs, Functions, AKS), GCP (Compute Engine, Cloud Functions), Terraform, CloudFormation, Docker, Kubernetes, Serverless Architectures, Load Balancing, CDN AI/ML & Data Engineering: Core ML model, RAG LLMs, TinyML (edge-computing), PyTorch, TensorFlow, XGBoost, SHAP, LIME, Apache NiFi, FHIR, Kafka, GridSearchCV, Multilabel Classification, Event-Driven Pipelines Backend & Microservices: C#.NET Core, Python (Flask, Django), Node.js, SQL (PostgreSQL, SQL Server), NoSQL (MongoDB), Prisma, Microservices, RESTful & gRPC APIs, CI/CD (GitHub Actions), Containerized Workflows Frontend & Web: Next.js, React, Tailwind CSS, HTML5/CSS3, JavaScript/TypeScript, Responsive UI, Vercel, Render Developer Tools & Collaboration: Git/GitHub, Docker Compose, JIRA, VS Code, PyCharm, Eclipse, Jupyter, CI/CD Pipelines, Agile/Scrum Practices I’m passionate about microservices, serverless architectures, advanced data-engineering to drive measurable impact and about driving AI-powered innovation in cloud environments—building robust ML pipelines, automating workflows, and deploying high-availability services. Let’s connect!