Credit Card Fraud Detection
- Trained machine learning model to detect credit card frauds, created a web application and deployed the model using AWS EC2 Instance.
- Tech stack: Python, Flask, HTML.
Secure E-Voting
- Worked in a team of 5 to implement two protocols for a secure e-voting system -
- Using only a Central Tabulating Facility - ensures authentication.
- Using blind signatures and CTF - dissociates the voter from the vote while still maintaining the authentication.
- Tech stack: MERN stack.
Cryptography Algorithms
- Implemented the Atbash cipher and DES algorithm. Demonstrated the Avalanche effect with different hyper parameter choices and the effect of using weak keys in DES.
- Tech stack: HTML, CSS, Javascript, Django.
Hyperspectral Image Compression using Non-negative Tucker Decomposition algorithm
- Compressed a 3D tensor, png image and real-life hyperspectral image datasets using the Non-negative Tucker Decomposition Algorithm.
- Tech stack: Python.
Question Answering on SQuAD 2.0
- Trained unsupervised and supervised machine learning models for the SQuAD1.1 dataset, a collection of question-answer pairs, with the correct answer being a sequence of words in the given context.
- Tech stack: Python.
Rumour Minimisation in Social Networks
- Studied how social networks can be modelled as graphs, various models of rumour spread in social networks and the "Greedy and Dynamic Blocking algorithms" to minimise their spread.
- Exposure: Graph theory.
I am a student at IIT BHU, Varanasi studying Mathematics and Computing, currently in my 5th year.
During the course of my college, I have been a part of various software development projects through coursework, internships and hackathons at Visa, Google and Infosys.
I love to explore various technologies, get hands on experience in them and aim to apply my knowledge on how they can be put to use to make our daily lives easier.
Apart from work, I enjoy photography, yoga and gardening. I also spend my time volunteering at Kashi Utkarsh, where we educate and spread awareness in the underprivileged sections of the society.