Vicent Gilabert Mañó

Vicent Gilabert Mañó

Data Scientist / Computer Vision Engineer

Cognizant

About me

I am currently employed as a Data Scientist specialised in Computer Vision at Cognizant, where I design and implement ML/software solutions for various companies.

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

 
 
 
 
 
Cognizant
Data Scientist
May 2024 – Present Remote
AIA: Artificial Intelligence and Analytics. Incorporating GenAI into the field of document analysis.
 
 
 
 
 
SEDDI
Computer Vision Research Engineer
September 2022 – May 2024 Remote
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.
 
 
 
 
 
AUTIS INGENIEROS
Junior Computer Vision Engineer
September 2019 – September 2021 Gandia (Valencia)
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.
 
 
 
 
 
Pattern Recognition and Artificial Intelligence Group | University of Alicante
Research Internship
October 2018 – February 2019 Alicante
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

 
 
 
 
 
Universidad Rey Juan Carlos
MSc in Computer Vision
September 2021 – June 2023

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.
 
 
 
 
 
Universitat d'Alacant
BSc Telecommunications Engineer (sound and image specialisation)
September 2014 – September 2019

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
September 2012 – June 2014
 
 
 
 
 
Technician in Microcomputer Systems and Networks.
IES Maria Enriquez
September 2010 – June 2012

Accomplish­ments

Coursera
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 certificate
Git and GitHub. A version control system from scratch.
See certificate
DataCamp
Intermediate Python for Data Science
See certificate
Introductionn of Deep Learning