I'm a Computer Science undergraduate (2023-2027) who enjoys solving real problems with code. I work mainly with
Python and C++, and I like writing clean, efficient programs.
I've built projects that combine software development with
AI — from small experiments to full applications — and I'm currently diving deeper into machine learning, NLP, and how
data can be used to make better decisions.
I care about understanding how things work and fit in the machine, and I’m
always trying to improve the way I think about design, performance, and reliability in code.
HTML
CSS
JS
REACT
NODE
PYTHON
SKLEARN
TENSORFLOW
LANGCHAIN
LANGGRAPH
GIT/GITHUB
DOCKER-
Credit Card Fraud Detection using Transformer models (Link)
Built a credit card fraud detection system using a range of machine learning models on highly imbalanced data. Developed a Transformer-based model, leveraging multi-head attention to capture complex relationships in transaction features. -
NLP-Powered Note-Taking Application (Link)
Built a GUI app using custom TF-IDF and TextRank pipeline to summarize 300–500 word notes in under 2 seconds, enabling real-time usability for students and researchers -
C++ neural network (Link)
Implemented forward/backpropagation, ReLU, softmax, and mini-batch gradient descent to achieve ~90% accuracy on Fashion-MNIST, with model serialization and modular design for deployment. -
Smart Health Record Management System (Link)
Built a secure, AI-driven healthcare platform with role-based access, patient record management, and automated medical summaries using React, Express, and Gemini API for data-driven doctor recommendations. -
ENIGMA Tech Fest Platform (Link)
Co-developed and deployed a full-stack portal for 500+ students, building responsive React components integrated with backend APIs for real-time event registrations and announcements.
