Welcome to my coding journey!
Computer Science Student skilled in software development, AI models, and a deep appreciation for mathematics.
Check out my LinkedIn ¡Chema's LinkedIn page!.
I was part of a team that developed ForestForecast, an award-winning web platform designed to predict and visualize areas at high risk of illegal deforestation using satellite imagery and historical data from NASA, alongside Google Earth. This project won GuadaHack, one of Mexico's top hackathons.
Utilizing advanced machine learning models, we achieved an accuracy of 88% in identifying regions susceptible to deforestation. Our platform integrates seamlessly with backend services using Flask and is deployed on AWS, ensuring robust real-time data processing and scalability.
ForestForecast not only highlights at-risk areas but also enhances global conservation efforts by providing accessible, interactive, and insightful data visualization to a wide audience, including environmental agencies and local authorities.
At BrainyPad, we are transforming the way students study by turning notes into interactive quizzes. Our application uses Retrieval Augmented Generation (RAG) to quickly search and generate quizzes that are precisely tailored to the learning content. This not only reduces study time but also significantly improves retention.
Developed EmoCare, an app that identifies user emotions through a convolutional neural network and provides personalized responses. Built using React Native and NestJS, the app integrates OPENAI and Google Text-to-Speech for interactive voice responses. A dataset of around 5000 labeled images trained the neural network, achieving high precision in emotion detection. Firebase was utilized for effective data storage and retrieval, ensuring smooth user experience and data management.
Won first place at the Bosch VISION IO hackathon with our image recognition application, which boasts a 94% accuracy rate in evaluating images from car rear cameras. Utilizing Python, OpenCV, and Streamlit, we developed a practical solution that applies image evaluation techniques and machine learning to address real-world issues in automotive safety. Our efficient teamwork and innovative approach accelerated development by 15%, enhancing the ADAS camera evaluation process.
This project allows seamless conversation with a digital assistant. Developed using React Native with TypeScript for the frontend, NestJS was chosen for managing backend requests and responses. To ensure optimal functionality, I integrated the OpenAI API and Google Cloud's Text-to-Speech API. Throughout the project's development, I gained valuable experience in leveraging NestJS for improved frontend interactions. This project also sharpened my mobile software development skills and introduced me to various new technologies.
This application serves as a real time shopping platform developed with React Native and seamlessly integrated with Firebase, offering real-time updates for both buyers and sellers. Beyond its efficiency-boosting features, it has been an immensely enriching learning experience. Throughout the development journey, I've gained valuable insights into database management, connecting applications to Firebase for dynamic data synchronization, and exploring emerging technologies. This project has been very beneficial for my skills and knowledge about mobile app development.
This project is centered around an emotion expression detection model, employing a Convolutional Neural Network (CNN). I trained the model using a dataset of roughly 5000 images, classifying them into seven emotions (e.g., happiness, anger, sadness). Leveraging Keras alongside NumPy and Pandas for data analysis and model training, I achieved a commendable 75% accuracy rate. All work was executed on my personal laptop, deepening my understanding of convolutional networks.
I had the privilege of working on a Sudoku-solving project using Python, implementing backtracking algorithms to create an AI-driven solver. The solver consistently provided solutions within seconds. An integrated screenshot analysis feature enhanced user experience for Sudoku enthusiasts. This project sharpened my algorithmic skills and creative problem-solving.
Experience the Snake Game Project—a technical feat in game development using HTML5, JavaScript, and the Canvas API. This project tackles game logic, UI design, animation, event handling, and audio integration to offer an engaging and challenging web-based gaming experience.
An OOP-based Snakes and Ladders project where classes represent game elements like board, snakes, ladders, and players. This approach enhances code organization, flexibility, reusability, and modularity for complex applications.
Conducted a comprehensive analysis of the SARS-CoV-2 genome using R for data analysis and genomic sequencing. Relevant mutations were identified to aid in developing effective therapies and vaccines, contributing to a better understanding of the virus’s evolution.
Developed a website offering a diverse selection of filters for image modification. Users can upload images and apply filters, utilizing technologies such as JavaScript, HTML, and CSS.
Part of a 5-person team for the NASA Space Apps Challenge, developing an innovative blockchain-based app with TypeScript, Figma, and React to securely disseminate scientific articles.
Created a Todo List app using TypeScript, HTML, and CSS with additional APIs to enhance functionality, enabling users to manage daily tasks and schedules efficiently.
A web page that lets users apply a green screen filter by uploading a foreground image (with a green background) and a background image. Developed using JavaScript, HTML, and CSS.
A simulation program using Python that allows users to observe the behavior of a vector field generated by point charges, offering an interactive physics exploration.
