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Achievement: Pull Sharkx2Achievement: QuickdrawAchievement: YOLO
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SaihajGulati/README.md

👋 Hey, I'm Saihaj - @SaihajGulati

  • 🌱 I have a passion for connecting people through innovative tech.

  • 👀 I’m looking for software and machine learning opportunities that have a direct impact on people and customers.

  • ✨ Below you can find some of the software and machine learning projects I am most proud of. Some of my projects are private because of academic and institutional protection, but feel to free to reach out! I'd love to chat about or even possibly demo these.

  • 📫 How to reach me: saihaj.gulati@gmail.com

  • ⚡ Linkedin: www.linkedin.com/in/saihaj-gulati

  • 💼 Portfolio: saihajgulati.com/

Pinned

  1. FindASeat FindASeat Public

    An Android application that helps users find and book seats in various buildings around the University of Southern California campus. Users can browse different buildings, check seat availability, …

    Java

  2. HuntTheWumpus HuntTheWumpus Public

    This is a complete Java game with more than 30 rooms and full theming built by Saihaj Gulati (Team Manager), Raj Sunku, Daniel Popa, Joshua Venable, Brian Yang, and Hans Koduri.

    Java 1

  3. seva-app seva-app Public

    A full-stack app to enable affordable mass communication between nonprofits and the people they serve. Utilizing Next.js, React, Tailwind CSS, Supabase, Twilio. Started in July 2023.

    TypeScript 1

  4. listening-party listening-party Public

    A full stack web application that allows people to join "listening-parties" in which they can chat with others, queue songs, and watch and hears music videos of those songs. Built with HTML, Javasc…

    Java

  5. amazon-remake amazon-remake Public

    A remake of the backend of Amazon, with a data store, full search and purchasing functionality, and different responses based on the type of product. Built entirely with C++ with manual memory mana…

    C++

  6. flower-find flower-find Public

    I use the python machine learning library sckit-learn to train a perceptron and decision tree to classify flowers, and a feedforward neural network for regression prediction on concrete strength da…

    Jupyter Notebook