Christ University Road, 30 Valor Court At Post: Dasve Lavasa,Taluka: Mulshi Pune 412112, Maharashtra.

Focus : Sustainability, Automation

Specifications : Machine Learning, IoT

Skills

Python, MS Excel, Machine Learning, Statistical Analysis, Full Stack Web Development, SQL, Data Analysis & Visualization, PowerBI, Basic Java, Basic C++,

Languages

English, Malayalam, Tamil, Hindi,

Summary

A curious data practitioner with a strong foundation in programming, statistics, data analysis, and web development. Actively seeks opportunities to learn from every project, with a proven ability to quickly adapt to new challenges. Passionate about IoT, web development, and sustainability.


Education History

M. Sc Data Science - 85 %
2023-08 / 2025-06
Christ(deemed to be) University, Pune Lavasa Campus, India
B.Sc Mathematics - 89 %
2020-08 / 2023-04
Madras Christian College, Chennai, India
High School - 94 %
2018-04 / 2020-04
GEMS Our Own English High School, Al Ain, UAE

Projects

BuildR - Project Management App
2024-08 / Present

An intelligent project management app to facilitate collaboration within teams. Features include : Team morale analysis, Task tracking, Data Visualization with detailed insights, Role-based Access controls, Comments for tasks and notifications.

Handled database designing, frontend & backend implementation, sentiment analysis, asynchronous task queue implementation and data visualization.

HungryStudent
2024-04 / 2024-06

A web-app aimed for accessing the menu of college canteens and restaurants around nearby campus so students can view and order food. Aimed at reducing queues during rush hours. Provides detailed data analysis for users as well as restaurants implementing the system.

Handled various aspects of the project including ideation, database designing, frontend and backend implementations  and testing. 

View GitHub Repo

 

Predictive maintenance of machines, using C-MAPSS dataset
2024-04 / 2024-06

This project was a collaboration between machine learning enthusiasts from various domains. The aim was to predict the failure of NASA engines ahead of time. Handled exploratory data analysis and machine learning model building and testing. Gained experience in deploying ML models to Azure web apps.

View Deployed Model - https://predictivemaintenance30daysml.azurewebsites.net/

View Project Documentation