Computer Science professional specializing in AI-driven medical imaging, DevOps practices, and cloud infrastructure. With a strong foundation in deep learning (CNN, Grad-CAM), Python, and full‑stack development, I build intelligent, scalable solutions that bridge the gap between research and production.
As a Computer Science professional focused on AI/ML and DevOps, I bridge development and operations to create streamlined, automated workflows. My expertise spans deep learning, cloud infrastructure, containerization, CI/CD pipelines, and system automation.
Currently advancing my skills through AWS Academy Cloud Foundations, I combine practical experience with continuous learning to implement modern, production‑ready AI solutions.
Custom CNNs, Transfer Learning, Grad‑CAM explainability, medical image classification
AWS services, VPC design, security implementation, and cost optimization strategies
Pipeline design, Jenkins configuration, deployment automation, and workflow optimization
2022 - Present | Current: 7th Semester
Cloud architecture, EC2, S3, IAM, VPC, security models, cost optimization
In ProgressNetworking fundamentals, TCP/IP, subnetting, routing & switching protocols
CompletedData pipeline architecture, analytics systems, ETL processes
DataCamp CredentialedShowcasing practical implementations of AI/ML, DevOps, and cloud technologies
Designed and implemented an end-to-end CI/CD pipeline using Jenkins for automated testing and deployment. Configured Docker containers for application isolation and built automated workflows from source control to production deployment.
Project inquiries: Available for similar implementations
Discuss ProjectArchitected scalable cloud infrastructure on AWS with focus on security and cost optimization. Implemented VPC configurations, IAM policies, and automated deployment of EC2 instances with S3 storage integration.
Project inquiries: Open for cloud architecture projects
Discuss ProjectBuilt automated data extraction and processing pipelines for large-scale datasets. Implemented web scraping solutions with error handling and data cleaning workflows for analytics-ready data preparation.
Project inquiries: Available for data pipeline development
Discuss ProjectDeveloped AI-powered applications with integrated chatbot functionality and language model implementations. Created RESTful APIs for AI service integration and deployed scalable solutions using Flask framework.
Project inquiries: Open for AI integration projects
Discuss ProjectA full-stack medical imaging platform using a custom CNN to classify brain MRI scans into four categories: Glioma, Meningioma, Pituitary, and No Tumor. Integrates Grad-CAM for explainability, providing visual heatmaps of tumor regions. Achieved 86% accuracy with 97% recall for pituitary tumors. Built with Next.js, FastAPI, and PostgreSQL.
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