It is a simple recipe app that comes with data populated with firebase. It is a how-to cook app complete with recipes required to fully cook a specific dish. Its data migration is so simple that with just a few tweaks in its columns/fields you can import any recipe data available on the internet.
Another feature is its ability to list and save the key ingredients needed for a specific dish that you wish to cook in just a single click. This simple and yet handy app is a must-have for all food lovers out there who are in the process of learning how to cook any recipes found on the app.
It’s a simple and straightforward chat application and has the functionality of sending text messages that will be automatically deleted within 24 hours for the initial version.
For the first version app release, we are planning to provide the key features and the main infrastructure of the app. Functionality and Process flow will be its main priority.
For the API we are going to be using Codeigniter and MySQL for the database hosted by Namecheap servers. This will also be using HTTPS protocol for all connection requests and communication to the server.
This is the new design for 2021, first prototyped in Figma and implemented by our volunteers.
This volunteer, with a background in Computer Science, decided to make a web app that can give guidance and direction on what to do if you're not feeling mentally well. One of the methods he implemented in the web application that utilizes React and HTML, there4u, is the guidance for box breathing.
Deploying an open source full stack serverless application to search, sort, and filter the public records on AWS, with CI/ CD (continuous integration, continuous deployment) workflows.
Link ProjectDeveloped using a popular JavaScript Framework, React. React Bootstrap library is used for UI components. The frontend is configured to redeploy on every repository push on the main branch. Github repository for the front-end source code:
Developed using Node.js, Express, and Serverless frameworks, and deployed on AWS Lambda. The REST API is developed using AWS API Gateway at this base url (https://q60xzpit4j.execute-api.us-east-1.amazonaws.com/dev). No API Key is required to access the API endpoints at the moment. The backend is also configured to deploy on every repository push on the main branch, using GitHub Actions. Github repository for the back-end source code:
The serverless database is up and running on AWS RDS with PostgreSQL-compatible Aurora engine. The database is publicly accessible with the correct host, username, and password. Only the reader instance is used with the application since the application does not require create, update, delete operations.
This volunteer worked on a lot of projects during his time with the program. He created a number of games such as a snake game, pong, cross road, and many other using Python. I also improved my skills using C language and object oriented programming.
This project focuses on building a game from scratch in C++ without external libraries or game engines. It consists of implementing the game simulation logic, resource management, often hidden functionalities (such as graphics), and integrating on the Windows platform. Currently, it can bring up a Windows graphical application and render primitive shapes, such as rectangles, concerning user inputs (such as mouse clicks). Future work includes supporting more keystrokes, rendering shapes, and interesting game logic.
RND4IMPACT.com 5.0 , the new design for 2023, first prototyped in Figma and implemented by our volunteers.
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The Project name was "SafeSecretShare". We often need to share sensitive credentials such as account passwords, credit card information, and API credentials with our friends, family, and co-workers. While sharing credentials, we often rely on the security of communication methods such as email and messaging apps such as WhatsApp, Signal, etc. These communication methods are not designed with the safety in mind of sensitive credentials and do not allow security features such as limited-time viewing, automatic deletion, IP address filtering, etc. The project's main idea is to enable users to securely share sensitive credentials.
I have created a back-end repository in Golang containing APIs to store encrypted messages. Github
You can find more about the project's technical description in the following Google doc:
This Python project implements ideas and problems from the space of quantitative finance. Some simple quantitative problems with theoretical results will be empirically verified using simulation. Some complex problems will also be simulated.
The goal of the project is to simulate ideas from simple problems to more complex problems. Optimization techniques will be implemented to improve the runtime and space complexity.
Machine learning, reinforcement learning, constraint optimization, etc. ideas will be implemented soon. Github
Fullstack project after the onboarding process until the 9th week. Implemented both front-end interface and back-end server with JavaScript and deployed the code to GitHub with a demo link and introduction.
Overview: The front-end interface was coded in JavaScript and deployed to Vercel with a user-friendly interface with the purpose of making easier process for user to book a hotel room. The back-end server was first deployed to AWS (but also local) and write the database to the MongoDB. The database will keep track all the data such as the guest information, room information, etc ... Each customer will have their own accounts to make reservation and can check back to past or the current reservation with the total amount of money for each reservation. The user can also leave a review if they want to share their experience to other customers.
Fullstack project from week 10 until week 19. Implement the front-end interface in JavaScript and the back-end server in Java. The project allows users to upload multiple database files then visualize the data in different charts and also make predictions for the users if necessary.
Overview: The front-end interface was coded in JavaScript and deployed to Vercel. Friendly interface allows user to upload multiple database files (currently there are 3 types of data file supported) and they can choose what type of plots they want to display the information. The back-end server was coded in Java and Python to process requests sent from the front-end interface. The Java back-end server used to process and arrange data for displaying purpose meanwhile the Python back-end server used to for predicting purpose.
Last project from week 20 until the end (week 22). Implement front-end in JavaScript and integrate the weather interface online to look for information on the real-time data on the weather.
Overview: The project mostly focus on creating a user-friendly interface for a weather application and integrate some onlines API to help looking for information about real time information. The website was deployed to Vercel with the link: 
This project is a set of APIs for the library management system. It has endpoints for different – books, author, borrowers. It also has support for data validation using middleware.
Project Descriptions 
Voting management application is an API based service. There are endpoints exposed for both Polls and Votes. Security with JWT authentication is also implemented. Middleware is used for error handling and also prevention of unauthorized manipulation including uniqueness of votes. The real-time updates for voting counts was done using Socket.IO/SignalR software for .NET.
Project Descriptions
It takes location as the input and displays information about its weather. It also has CSS to support styling. OpenWeatherMapp API is used to get more accurate and granular weather information. It also has weather forecast option using the same API.
Project Descriptions
Javascript based questionnaire paired with HTML. It also has CSS and styling components, which are easily configurable. There is also a component for random question generation. The score is displayed at the end.
Project Descriptions
The first Computer Vision project I conducted in 2024 was Iris Classification, a classic machine learning project in Kaggle or Dacon. As a Volunteer Software Engineer, I have implemented image classification models that classify different types of iris flowers. This project explores classifying Iris flower species (Iris setosa, Iris versicolor, and Iris virginica) using machine learning algorithms. For this project, I employ the classic Iris dataset and investigate the efficacy of different classification models, including supervised and unsupervised learning. The analysis includes data exploration, model training, evaluation, and final selection of the best-performing model.
Project Descriptions
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