Open Source Impact
114+ merged pull requests across 5 production repositories — security, concurrency, AI, cloud, and backend systems.
Merged PRs
Production Repositories
Eventra
PROBLEM
Implemented Redis-backed distributed rate limiting eliminating instance-hopping bypass attacks.
SOLUTION
500+ concurrent requests supported.
AegisGraph
PROBLEM
Eliminated race conditions across async services in runtime state management.
SOLUTION
Synchronized shared runtime state across async services.
pdf-qa-bot
PROBLEM
Resolved concurrent model execution failures in the RAG inference pipeline.
SOLUTION
Reliable parallel document processing under load.
Featured Work
Full-stack applications, ML systems, and cloud architectures built with production-grade patterns.
Full-Stack Career Development Platform with gamified learning, MCQ + coding exams, AI-powered resume generation, and a coin-based reward store. Built with Django, DRF, PostgreSQL, and WeasyPrint for PDF generation.
Built async resume/PDF generation with RBAC-backed learning workflows.
Key Engineering Challenges
Fully serverless AWS application for secure note and file management. Uses Lambda + API Gateway for REST APIs, S3 pre-signed URLs for file I/O, DynamoDB for storage, Cognito for auth, and CloudWatch for monitoring.
Shipped secure serverless notes and file storage with Cognito and S3 pre-signed URLs.
Key Engineering Challenges
AI-Powered HR Intelligence Platform built for a hackathon. Features DRF APIs, async ingestion pipelines via Celery + Redis, PostgreSQL models, React dashboard, and Dockerized deployment.
Designed async HR intelligence pipelines with Celery, Redis, and Dockerized services.
Key Engineering Challenges
Deep learning project classifying images into 15 animal categories using MobileNetV2 transfer learning. Features data augmentation, early stopping, and a Streamlit web app for predictions.
Trained and deployed transfer-learning inference for 15-class image classification.
Key Engineering Challenges
ML web app that analyzes and visualizes dominant color distribution in images. Uses Random Forest classifier on custom-labeled color dataset with OpenCV for feature extraction and Streamlit for the UI.
Delivered real-time dominant-color prediction with OpenCV feature extraction.
Key Engineering Challenges
Recognition
Competitive programming, open source recognition, and certifications.
LeetCode Rating
Problems Solved
CodeChef Rating
GSSoC Rank
Amazon ML Challenge
OCI Certifications
LeetCode profile · Codeforces 1364 · CodeChef 4★
Academic Background
Computer science and engineering degrees.
B.Tech Computer Science and Business System (CSBS)
Diploma Computer Engineering
Technical Expertise
A living visualization of connected technologies floating in space.