I'm a computer science graduate student at Arizona State
University
actively looking for full-time opportunities starting
May 24
Hey! It's Arshdeep Singh and I'm a student with Frontend Web Development experience, located in U.S. (Flexible to relocate nationwide / Remote). I've done projects for personal, research and production environment and collaborated with many talented individuals in my professional journey so far.
I have a can-do attitude and am willing to go beyond the initial expectations. I'm a bit of a technology junky and like to explore new digital products. Feel free to contact me here.
Developed a feature-rich application employing the MERN stack (MongoDB, Express.js, React.js, Node.js) and Socket.io. This application provides a robust and dynamic user experience by seamlessly integrating real-time messages through the private chats, allowing users to add emojis along with text and their messages are kept safe by using login authentication throughout the application.
Github LinkDemonstration of Data Visualization projects via interactive graphs and visualizations using CORGIS Global Development and Soviet Space Dogs dataset. They showcase proficiency in utilizing tools such as D3.js, Javascript, Bootstrap, CSS, and HTML.
Github LinkDeveloped a Twitter clone in Android Studio using Twitter's API in Java. Created a user-friendly interface with features like login, home feed, trending, follow, image uploads to tweets, and advanced options such as long-click actions and dark mode. The project demonstrates proficiency in mobile app development and object-oriented programming.
Github LinkThis project focuses on applying Deep Reinforcement Learning (RL) algorithms to train agents in two distinct environments provided by the Gym library: Cartpole and Humanoid. The Cartpole agent learns to balance itself, while the Humanoid agent learns to walk. I utilized the Stable Baselines3 library, Gymnasium, and MuJoCo for efficient implementation and realistic physics simulation.
Github LinkClassification of images into a number of classes (FashionMNIST dataset) using a CNN model. Additionally, adversarial attacks has been implemented on the model and the effected accuracy has been calculated. This demonstrates how minute changes in the images of training data can significantly impact the model's accuracy
Github LinkAnalyzing and comparing movie recommendation systems using Netflix customer ratings data. Evaluating methods like KNN, KMeans, DNN, and Matrix Factorization. Offering a user-friendly web interface for users to input movie/user IDs and receive recommendations for similar movies.
Github LinkA mobile app for the visually impaired includes a Braille keyboard for typing using gestures and buttons, with text-to-speech and haptic feedback. It also has an Object Detection module using a camera for real-time awareness through audio feedback. The app uses a MobileNetwork with SSD (Single Shot Detector) model to classify objects in images, aiming to improve daily experiences and promote inclusivity for the visually impaired.
Github LinkThe project centers around refining question creation by utilizing Reinforcement Learning to fine-tune a base Language Model. It evaluates and compares these novel approaches to assess their effectiveness and the improvements they introduce.
Github LinkThis project aims to assess if a code snippets found in online forums pose system threats. Using NLP for text summarization and Natural Language Inference, it checks for vulnerability keywords found in the generated summaries to determine the presence of potential threats.
Github LinkThe Phone Directory project showcases my proficiency in C++ programming, highlighting skills in memory management through pointers, the application of Object-Oriented Programming (OOP) concepts, and the utilization of complex data structures, including trie, hashmaps, and sets. In this project, I designed and implemented an efficient phone directory system with features such as insertion, deletion, and search functionalities.
Github LinkExplore a collection of Android games meticulously that provide an immersive gaming experience crafted in Java using Android Studio, showcasing my expertise in mobile application development along with a solid grasp of core Object-Oriented Programming (OOP) concepts like inheritance, abstraction, and polymorphism. Elevating the challenge level, Othello features an intelligent AI opponent that player can play against made using Minimax algorithm with alpha-beta pruning.
Github Link
