Software Engineer
Building scalable web applications, data pipelines, and applied AI/ML solutions.

Final-year CCE student at Manipal University Jaipur (8.5 CGPA). Building end-to-end solutions across Full-Stack Development, Applied Machine Learning, and Generative AI.
Software Development Intern
Research Intern

Database-driven ERP platform for managing KPI workflows at MUJ.
Designed and implemented a database schema and modular ERP layout tailored to university workflows at Manipal University Jaipur. Contributed to backend API development by building authentication routes and secure role-based access logic. Integrated departmental management and academic performance analytics into a scalable monorepo setup, leveraging modern frameworks for maintainability and performance.

AI agent with RAG, session memory, and plugin system built in a 1-day challenge.
Developed a modular conversational AI agent in TypeScript with a Node.js + Fastify backend. Integrated Retrieval-Augmented Generation (RAG) using Weaviate for semantic search, Google Gemini for reasoning, and a persistent memory layer for contextual conversations. Designed a pluggable architecture supporting tools like weather and math plugins, enabling dynamic extensibility.

Boosted churn prediction accuracy to 81.65% by building an ensemble model combining Gradient Boosting, Logistic Regression, and AdaBoost.
Developed a predictive analytics project targeting customer churn using an ensemble of Gradient Boosting, Logistic Regression, and AdaBoost. Achieved over 81% accuracy through rigorous preprocessing, feature engineering, and model tuning. Built a visualization pipeline to explain model outputs and improve stakeholder interpretability of retention strategies, highlighting actionable insights from data.

A server-side plugin based multi-lingual translation system for websites by extracting and translating content from the DOM.
Developed an in-house full-stack localization system capable of translating dynamic websites across 22 Indian languages. The system uses server side rendering for static pages and client-side script for dynamic pages to serve millions of users. A lightweight SQLite caching layer ensures sub-millisecond translations for repeated content, significantly improving and saving API calls to a self-hosted NMT model.
Meghneel Gogoi, Aditya Narayan Hati, Dinesh Kumar Saini
International Journal of Information Technology & Decision Making (IJITDM)
This work proposes a hybrid decision-making framework for test case prioritization (TCP) that integrates Intuitionistic Fuzzy AHP (IF-AHP) and VIKOR. IF-AHP is employed to derive robust criterion weights by capturing uncertainty, hesitation, and subjectivity in expert judgments, while VIKOR is used to rank test cases by balancing conflicting criteria and identifying compromise solutions. The framework is validated on a multi-criteria software testing dataset, demonstrating its scalability, efficiency, and suitability for practical quality assurance environments..