Building products and solutions that make a difference. Here's my journey so far.
4 positions
Collaborated with the founding team on developing production-ready products, focusing on dashboard development and full-stack integration.
Building a security automation platform using LLMs to detect threats across the SDLC. Working on frontend UI, Jira auto-ticket integration, backend pipelines, and training AI agents to streamline threat detection and reporting.
Working as a founding member of the company, I am responsible for developing and maintaining the company's products based on the latest AI/ML technologies and frameworks.
Collaborated with the founding team on developing production-ready products, focusing on building a secure and efficient systems.
Explorations in code that fuel my curiosity and growth
A distributed file system for storing and sharing files across multiple nodes.
A clone of code rabbit which uses AI to review the code, you can add all the github repo and it will review the code and give you the best possible review.
Postman clone with real-time updates and collaborative features web version.
Research papers and publications I've contributed to
As a result of recent advances in deep learning, several breakthrough stories in modern medical diagnostics with data-driven insights into improving healthcare facilities' quality of treatment have arisen. Deep learning methods that perform well are significantly data-driven...
With the rise in the amount of news available today, the need for its classification has emerged. In this paper, we present methods for tagging news categories using different deep learning models along with a comparison of their effects. These models include single-channel CNN model, multichannel CNN model, and multimodal CNN model...
Groundbreaking papers I'm currently reading or plan to read
Insights, discoveries, and deep dives from my daily learning adventures
Discover how transformer models like GPT work internally—from tokenization to attention mechanisms—and understand the key concepts behind large language models.
HTTP explained like you're building real backends — covering the protocol fundamentals, request/response cycle, headers, methods, status codes, CORS, caching, and security with TLS/HTTPS.