I build machine learning solutions that turn real-world data into useful predictions and insights. Currently working as a Machine Learning Intern at NES Technologies while pursuing B.Tech in Computer Science at Thapar Institute of Engineering & Technology.
A little bit about who I am and what I work on.
B.Tech in Computer Science
Thapar Institute of Engineering
& Technology
2024 â 2028
Machine Learning, anomaly detection, predictive analytics, time-series analysis, deep learning and MLOps.
Data-driven applications, ML models, predictive systems, intelligent automation and backend-powered applications.
I regularly practice Data Structures & Algorithms and competitive programming, mainly using C++.
My professional experience.
Working on machine learning solutions using
real-world datasets.
Current work includes theft anomaly detection,
predictive analytics, data preprocessing,
feature engineering and ML model development.
Some of the projects I've worked on.
A predictive maintenance system designed
to estimate the Remaining Useful Life (RUL)
of aircraft engines using the NASA CMAPSS
dataset.
The project uses feature engineering,
lag features, rolling statistics and
machine learning models.
An energy analytics project focused on
understanding building energy consumption
patterns using machine learning and
statistical techniques.
Includes clustering, PCA and exploratory
analysis.
A database management system for storing,
managing and verifying student certificates.
The project demonstrates database design,
CRUD operations and SQL/PLSQL concepts.
A personal AI assistant built with Python
that enables voice-based interaction and
automation.
The project explores speech recognition,
voice commands and AI-powered interaction.
Technologies and areas I work with.