Hi, My name is Aaditya Bhargav, a hard working and passionate student currently pursuing Masters from IIIT Delhi, specialized in Computer Science and Engineering. I'm curious of learning new technologies and try to make
something innovative from it.
I'm a Competitive Programmer, Full Stack Web Developer and a ML Enthusiast.
My primary focus, in the field of Computer Science lies in Web Developement and Machine Learning.
I am proficient in HTML, CSS, JavaScript, Bootstrap and beginner in ML, ReactJS and NodeJS.
Worked as a Software Developement Engineer. Worked on the frontend and backend development of an IoT dashboard web application using React JS and Flask (Python). Establishing the connection between IoT devices and servers using Rest API and MQTT. Also worked on the development of a Facial Recognition based Attendance application.
Worked as a AICTE Cybersecurity Intern. Build a Secure Campus-Area Network which aims to provide a safe, and reliable network environment for students, faculty, and administrative staff while safeguarding sensitive data and intellectual property.Structure of the network was divided according to various departments like students, faculty, and administration and used a routing algorithm to safeguard the network against cyberthreats.
Worked as a Full Stack Web Developer Intern. Developed and maintained a web application using a wide range of technologies, including HTML, CSS, JavaScript, Bootstrap, and jQuery. Designed and implemented scalable and efficient backend system using MySQL for database management and also utilized PHP as a scripting language to establish smooth communication between the front-end and back-end, ensuring data integrity and security
Used cv2, a computer vision machine learning library for performing image processing and computer vision tasks and built the frontend using React JS and backend using Flask
Built the frontend of the IoT monitoring dashboard using ReactJS, which uses Rest API to fetch the data from the IoT device and uses Flask forthe backend. The Rest API is built using Flask, which will be used to fetch the IoT data.
Developed a weather application using ReactJS to create a dynamic and responsive userinterface, enabling users to access accurate weather data quickly and efficiently.This application uses weather API to fetch weather data of different countries and display up-to-date weather data for a specified location.
It is a Machine Learning model which helps to predict an emoji based on the written text. A Machine Learning model which uses LSTM model and Keras layers to predict best possible emoji for the given text. It Uses an external package emoji, in order to show the emoji’s and apply glove vectors in order to convert the sentences into embeddings.
Build using ReactJS. It helps to prioritise the tasks that are more important. The web-based application will allow users to add, edit, mark as completed, and delete tasks. It helps individuals and teams to stay organized by providing a central place to list and manage tasks, ensuring nothing important is overlooked.