Projects#
Here are some of the projects I’ve worked on, demonstrating my expertise in AI, Machine Learning, Backend Development, and DevOps.
Hikari (2024-2025) (OSS)#
Hikari is a lightweight deployment manager that automates configuration updates, Docker Compose management, and cleanup for virtual machines by monitoring remote files. It simplifies deployment workflows, ensuring efficiency and reliability with minimal manual intervention. Built with Rust, Docker, WebSockets, and PostgreSQL, Hikari is a lightweight Kubernetes alternative for small-scale setups.
Read about Hikari Agent-Server Mode#
Read about Hikari Daemon Mode#
Hikari Source-Code#
Autodeploy (2024) (OSS)#
Autodeploy is a streamlined deployment automation tool that simplifies the process of deploying applications on servers with minimal configuration. It ensures hassle-free, consistent, and efficient deployments, saving time and reducing errors. Engineered in Rust, it integrates Git repository management and Docker containerization through an interactive user interface.
Read about AutoDeploy#
Autodeploy Source-Code#
Fetal Health Classification (2023)#
This project focuses on developing a machine learning model to classify fetal health risks based on Cardiotocogram (CTG) data, achieving a 97.8% accuracy. Built using Python with Scikit-Learn and SciPy, the solution involved extensive data cleaning, preprocessing, and evaluation across multiple algorithms. The application’s front-end is built with Angular and Flask, handling the backend, and the entire system is deployed on Docker for scalability and replicability in clinical settings.
Fetal Health Classification Source-Code#
Documan Web (2021 - 2024)#
Architected and scaled the Documan digital library platform, serving over 4,000 students with more than 200,000 file deliveries. The platform features a responsive web interface and an interactive Telegram bot, with a robust content management system and optimized file delivery. Built using Python, Flask, and PostgreSQL, and deployed with Docker.
GCTCPORTAL Bot (2022 - 2024)#
An internal automation tool that streamlines daily workflows by integrating with the Telegram Bot API and Google Workspace APIs. The tool reduced task completion time from 15 minutes to just 25 seconds. Implemented threading to parallelize uploads, reducing times from 1 minute to 15 seconds for larger files.
Visit GCTCPORTALOther Projects#
- College Fest Websites: Designed and developed official websites for VIBGYOR ‘22 & VIBGYOR ‘23 and BHASWARA ‘22 & ‘23.
- IOT Based Food Grain Storage Monitoring System: A prototype IoT system to monitor the conditions of food grain storage silos.
- Parking Lot Status Monitoring System: An Arduino-based project to monitor parking lot availability.
- Tessellation: My submission for the GCTCPORTAL 2021 Recruitment.
