Bachelor of Technology student
Bachelor of Technology student with internship experience in research, machine learning, and data analytics, supported by projects in fraud detection, NLP, forecasting, and dashboards.
Defence Research and Development Organisation (DRDO)
May 2025 – July 2025 · New Delhi, India
Contributed to research in radar systems and electronic warfare jammers at the ISSA Lab; used Python for data analysis and modeling and simulation to analyze system performance; collaborated with senior scientists on cybersecurity and information systems projects for national security applications.
CantiLever.in
June 2025 – July 2025 · Remote
Developed a credit card fraud detection model using XGBoost and Scikit-learn; built a sentiment analysis model using NLP, TextBlob, and WordCloud; implemented data preprocessing and visualization pipelines using Pandas, Matplotlib, and Seaborn.
Edunet Foundation
January 2025 – March 2025 · Remote
Designed an AI-powered outbreak prediction platform with machine learning models and interactive dashboards; performed data analysis using Python and SQL; applied statistical and machine learning techniques to public health challenges.
Career Development Cell, MAIT
October 2024 – Present · Maharaja Agrasen Institute of Technology, Delhi, India
Led placement coordination for more than 1000 students, managed recruitment drives and corporate relationships, and designed database systems for student records, company data, and placement analytics.
Bachelor of Technology, Electronics and Communication Engineering
2023 – Present
CGPA: 8.6/10.0
Developed a prototype for the Hack4Bihar semifinal using Python, NLP, TensorFlow, Scikit-learn, and Streamlit for carbon emission analysis and forecasting. Built weekly and monthly footprint monitoring with personalized tips and warnings, and integrated news sentiment analysis via API for environmental insights and recommendations.
Developed an integrated solution using Python, NLP, TensorFlow, OpenCV, FastAPI, and Streamlit to detect fake job postings and verify fraudulent certificates. Deployed Streamlit dashboards and FastAPI REST APIs, including interview preparation modules; NLP text classification achieved 92% accuracy in identifying fraudulent content.