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. We continuously refine BrainyPad by conducting user testing, ensuring it aligns perfectly with educational needs and real-world feedback.
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 the nuances of database
management, the process of connecting applications to Firebase for dynamic data synchronization,
and the exciting realm of emerging technologies. This project has been very beneficial for
my skills, fortifying my expertise in software development and my knowledge about
the mobile app technology landscape.
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 different emotions, such as happiness, anger, and
sadness. Leveraging Keras, alongside NumPy and Pandas for data
analysis, image dimension handling and the model training. I achieved a commendable 75%
accuracy rate. Remarkably, all this work was executed on my personal
laptop. Through this journey, I deepened my understanding of convolutional
networks and their learning processes.
I had the privilege of working on a Sudoku-solving project using Python, where I implemented backtracking algorithms to create
an AI-driven solver. The solver demonstrated commendable puzzle-solving capabilities, consistently providing solutions within seconds,
which I found rather satisfying. To enhance the user experience, I integrated a feature for screenshot analysis, seamlessly blending it with Python's
algorithmic execution. This addition ensured a more user-friendly interface for Sudoku enthusiasts, and it felt like a small but meaningful contribution.
Through this project, I had the opportunity to sharpen my algorithmic skills and explore creative ways to solve problems, which was a valuable learning experience.
Experience the Snake Game Project, a technical feat in game development. Built using HTML5, JavaScript, and the Canvas API,
this project tackled challenges like game logic, UI design, animation, event handling, and audio integration. Explore the fusion
of coding and design, offering players an engaging and challenging gaming experience. Dive into the world of web-based gaming and
witness the mastery of JavaScript, all wrapped up in this classic Snake Game.
Snakes and Ladders project using OOP. Classes represent game elements like board, snakes, ladders, and players.
Encapsulated logic for better organization. Solid design principles ensure flexibility.
OOP enhances code structure, reusability, and modularity. Powerful tool for complex apps.
I carried out a comprehensive analysis of the genome of the SARS-CoV-2 virus using data analysis and genomic sequencing tools in the R language.
We identified the most relevant mutations in terms of virulence, transmissibility, and resistance to available treatments. The information obtained
could be useful for developing effective therapies and vaccines against COVID-19, as well as for more efficient prevention and control strategies.
This study helps to understand the evolution and behavior of the virus over time, and the fight against this infectious disease benefits from the
research and results obtained.
I developed a website featuring a diverse selection of filters for image modification, allowing users to upload their own images and apply available filters to enhance them.
This project required proficiency in several key technologies, including JavaScript, HTML, and CSS.
I was part of a 5-person team that took on the NASA Space Apps Challenge hackathon. Together, we developed an innovative
blockchain-based app using TypeScript, Figma, and React. Our primary goal was to create a secure and transparent system for disseminating scientific articles.
The app leverages blockchain technology to establish an unalterable record of each article's
publication, guaranteeing the authenticity and source of every piece of scientific work. To make it user-friendly for scientists, we incorporated Figma and React to design an intuitive interface for publishing and sharing articles.
The potential impact of our app is significant. It could revolutionize the way scientific articles are published and shared, thanks to blockchain
technology ensuring the credibility and source of these articles. Moreover, by streamlining and adding transparency to the publication process, it has the potential to save scientists valuable time and resources.
I created the Todo List app as a tool to help users better organize their daily tasks. Using technologies such as TypeScript, HTML, and CSS, I developed this app with additional APIs to enhance its functionality. With intuitive task management and organization features, users can easily keep track of their to-do lists and stay on top of their daily schedules.
This is a web page that allows users to utilize a green screen filter. To use this feature, the user needs to upload a foreground image with a green background and a background image. This page was developed using web development technologies such as JavaScript, HTML, and CSS.
This is a to-do list app created using JavaScript, HTML, and CSS. The app aims to assist users in organizing their lives more effectively by providing an easy-to-use platform for tracking tasks and events.
This is an interactive paint web page that allows users to draw anything they want using a variety of colors and pen thicknesses. The page is created using JavaScript, HTML, and CSS to provide a seamless and enjoyable user experience.
This program is a simulation that allows users to observe the behavior of a vector field based on the interactions of point charges. The simulation is created using Python, providing an immersive and interactive experience for users to explore the laws of physics.
