Jaime Díez Rodríguez

trAIning uses AI and machine learning to create a full-experience workout application. It is able to track user activity, count workout reps, display interactive analytics, and host social interaction between users. Together with a team of 3 other people, my responsibilities included studying the feasibility of using Tensorflow.js according to our needs and implementing a nice UI/UX. I also played a key part adding ML models to this project, as well as building the project around the Firebase technology. The tech stack: This application is in Typescript. It uses Firebase for the back end. React, Less, Ant Design, Dayjs, React Webcam, Craco, TensorFlow, and TeachableMachine on the front-end. trAIning was deployed using AWS.

My Companion is a mobile oriented web application to keep track of your pets data, such as measurements and observations, and to schedule appointments, like vet visits and vaccinations. I played a key role refactoring the application to TypeScript and writing unit and integration tests, as well as cleaning and polishing the code, fixing some bugs and implementing modularity in the components. The tech stack: Chakra-ui, React, Jest, and Agenda on the front-end and Express, Parse-Server, Helmet, and Nodemailer on the back-end. Typescript on front and back.