Starting from the childhood I am interested in studies and always work hard. I am always open to opportunities and challenges which come in my way. In fact, I love to do things which people usually find difficult and may also not be able to do the first time but do not accept defeat until I reach my maximum limit of thinking.

Talking about achievements in school I have got many prizes in an annually conducted exam named MEC consisting of mathematical, logical and aptitude questions. I have got bronze medal for English Olympiad and was the class topper. I secured first rank till 5th standard and afterwards not first but always in toppers list. And in 12th I was the school topper. Also, after getting a decent rank in JEE, I got admission in one of the prestigious universities IGDTUW. Then, starting from the first semester I started practising Java questions in Hackerrank and got 5 star ranking. Also, I had practised C language and got 4 star in Hacckerrank for the same. I always remain active in finding opportunities, learning new things, improve my problem solving skills, practising DSA and building a admirable personality. Also, I have got the maximum scholarship from prestigious Reliance Foundation and I was one of the 5000 selected students from 40000 applicants.

Also, I have taken part in many hackathons and cohorts and learn some new things from every one of them. But few days ago in 12th Feb I got the 2nd runner up position in the famous IEEE hackathon WIEgnite of our university. This also taught me many things and motivation to learn more and expand my knowledge.

PROJECTS

EmoteCare
Implemented backend functionalities using Flask within a website designed to destigmatize mental health and
improve accessibility to therapy.
Incorporated AI-driven facial emotion detection for real-time insights, tackling societal taboos and financial
barriers by combining datasets and utilized TensorFlow CNN, achieving a model accuracy of 66.45%.

Side-Scrolling-Platformer
Developed a classic side-scrolling platformer inspired by Mario, featuring challenging obstacles and interactive
objects using Unity and C#.

TED Talks Web Scraped Dataset
Conducted Exploratory Data Analysis to gain insights into the dataset, followed by the application of Multiple
Linear Regression to analyze the relationship between factors such as duration, views, and likes of TED Talks
videos.
The model achieved an impressive accuracy of 99.96%, demonstrating its effectiveness in predicting the influence
of these factors on video performance.