I'm a Computer Science graduate from CUNEF University, passionate about software development, artificial intelligence, and cybersecurity. I specialize in creating innovative technological solutions while staying committed to continuous learning and improvement. I'm looking to be part of challenging projects that combine technology and creativity to solve real-world problems.
- Programming Languages:
- Frontend: HTML, CSS, JavaScript.
- Backend: PHP, Python, Java, C, C++.
- Frameworks and Web Technologies:
- Client-side: React, AJAX, jQuery.
- Server-side: Node.js, Express.
- APIs: Design and testing with Swagger OpenAPI, Postman.
- Databases: MySQL, Oracle, SQL Server, MongoDB, Cassandra, Neo4j.
- Artificial Intelligence and Neural Networks:
- Design and training of neural networks with TensorFlow and PyTorch.
- Application of CNNs and RNNs in image classification and data analysis.
- Implementation of supervised and unsupervised machine learning models.
- Data Analysis and Data Science:
- Pandas, Numpy, Scikit-Learn, NLTK (Natural Language Toolkit), R, MATLAB, Maple.
- Development Tools and Environments: Git, GitHub, Visual Studio Code, XAMPP, LaTeX.
- SpotifySongRecommender: A C++ project for analyzing and recommending songs. It includes features like recommending songs and artists based on musical genres, and generating popularity rankings by artist or genre.
- Machine Learning Client Project: Data analysis for a client using machine learning. The project includes data preprocessing, feature selection, model training, hyperparameter tuning, and evaluation using metrics relevant to the client's business goals.
- Pathfinding Algorithm (A*): This Python project implements the A* algorithm to find the optimal path in a randomly generated 2D matrix with obstacles. It allows users to choose between Manhattan and Euclidean distances for the pathfinding process. The matrix, along with the calculated path, is displayed on the console.
- Parallel-SwarmOptimization-Project: A Python project that implements and compares several variants of the Particle Swarm Optimization (PSO) algorithm using different parallelization strategies (threads, processes, asyncio, and a combined approach). Includes a full execution time analysis in Jupyter Notebook.
- Biblioteca API REST: REST API for managing a book library, with CRUD functionalities, Swagger documentation, and MongoDB connection using Mongoose. Developed with Node.js and Express.
- Bachelor's Degree in Computer Science: CUNEF University (2021–Present).
- Specialization in Computing.
- Honors in Artificial Intelligence and Machine Learning.
- Cybersecurity Certification: Hacking School I & II (U-tad, 2017).
- 📧 Email: juancarloseovejero@gmail.com
LinkedIn: Juan Carlos Estefanía Ovejero
GitHub: jcestefania
