About me
I am currently employed as a Computer Vision Research Engineer at SEDDI, where I contribute to the research and development of computer vision algorithms to enhance the functionality and technology of Textura.ai.
Interests
- Computer Vision
- Artificial Intelligence
- Neural Networks
- Software development
Education
MSc in Computer Vision, 2021
Universidad Rey Juan Carlos
BSc Telecommunications Engineer, 2014
Universitat d'Alacant
Experience
Computer Vision Research Engineer
The Optics, Rendering, and AI Department focuses on advancing Textura.ai through cutting-edge research and development in computer vision. This involves exploring diverse areas such as image retrieval, quality assessment, and restoration, while continually assessing the latest advancements in the field. Utilizing tools like Python, PyTorch, OpenCV, and various libraries, the team trains and evaluates deep learning models to enhance Textura.ai’s capabilities, ensuring its position at the forefront of technological innovation.
Junior Computer Vision Engineer
In my role within the Department of Computer Vision and Signal Processing Systems, I’ve been primarily engaged in commissioning computer vision systems across various industries. Noteworthy projects include commissions for Ford Valencia in Spain, Toyota Kentucky, Toyota Indiana, and Nissan Mississippi in the United States. These assignments have allowed me to apply my expertise in optimizing and ensuring the smooth operation of computer vision systems within industrial settings.
Optical Music Recognition (OMR) encompasses the utilization of computer vision, machine learning, and neural networks, with a particular emphasis on Convolutional Neural Networks (CNNs). One of the core tasks involves image labeling to construct a comprehensive OMR dataset. To accomplish this, essential tools such as Python, TensorFlow, Keras, OpenCV, Numpy, and MATLAB are employed, facilitating the development and refinement of OMR algorithms and systems.
Education
MSc in Computer Vision
GA: 8.9 / 10.0
- Image and video processing, machine and deep learning, biometrics, robotics, 3D vision, medical image.
- Python, OpenCV, Numpy, SciPy, Keras (TF), MATLAB, matplotlib, pandas, etc.
BSc Telecommunications Engineer (sound and image specialisation)
GA: 7.0 / 10.0
- Subjects included: Maths, Physics, circuits and electronics, communications, signal processing, image processing, audio processing, acoustics, microcontrollers, networks, etc.
- Exchange year at: Universidad Técnica Federico Santa María (Valparaiso - Chile)
- Subjects: Computer Vision, IT Project Management, Antennas and Propagation, Wireless Networks.
Higher Technician in Administration of Computer Systems and Networks.
IES Maria Enriquez
Technician in Microcomputer Systems and Networks.
IES Maria Enriquez
Projects
*
Accomplishments
Machine Learning
Offers a concise yet comprehensive overview of fundamental machine learning concepts and techniques. Through video lectures, quizzes, and programming assignments, learners explore topics such as linear regression, logistic regression, neural networks, support vector machines, and unsupervised learning. The course emphasizes practical implementation, with interactive exercises in MATLAB or Octave, and covers applications like recommender systems and large-scale machine learning.
See certificateGit and GitHub. A version control system from scratch.
See certificate
Intermediate Python for Data Science
Introductionn of Deep Learning
Contact
Get in touch!