Mario Parreño

Hey! I'm an artificial intelligence researcher in Spain, interested in machine learning, computer vision, trying to materialize the networks with some projects!

What I am all about

I completed a Bachelor's Degree in Informatics Engineering and later a Master's Degree in Artificial Intelligence, Pattern Recognition, and Digital Imaging at the Polytechnic University of Valencia (Spain). Now I am doing my Ph.D. in Computer Vision relating to domain adaptation and transfer learning under medical image segmentation constraints. I like to compete in Kaggle competitions where I try to win other scientists from all over the world, where little by little I am learning, but I often delve into other hobbies such as music and sports.

I'm currently researching various areas of machine learning, computer vision, and artificial intelligence. You can see all my publications here.

Work Experience

  • 2019 - Present Computer Vision Engineer Universitat Politècnica de València (UPV)

    I am working in ​​Computer Vision on a project for PAVASAL S.A. in the automatic recognition through images of different asphalt damages.

  • May 2019 – Sep 2019 (5 mos) Machine Learning Engineer Universitat Politècnica de València (UPV)

    Deep-Learning and HPC to Boost Biomedical Applications for Health at the European project "European Distributed Deep Learning Library".

  • 2018 - 2019 Associate Research Fellow - Computer Vision Universitat Politècnica de València (UPV)

    Research in state-of-the-art convolutional neural topologies at PRHLT Research Centre.


  • 2019 - Present PhD, Machine Learning Universitat Politècnica de València (UPV)

    I am studying techniques of transfer learning and domain adaptation under medical imaging constraints.

  • 2017 - 2018 MSc in Artificial Intelligence Universitat Politècnica de València (UPV)

    Master's Degree in Artificial Intelligence, Pattern Recognition and Digital Imaging.

  • 2013 - 2017 Informatics Engineering, Computer Science Universitat Politècnica de València (UPV)

    Bachelor’s Degree in Informatics Engineering with a mention in computation.


  • 2021 Datathon Cajamar Universityhack Cajamar Datalab - 3 of 32

    I had created of a web dashboard to analyze the behavior of the Spanish fruit and vegetable market during the pandemic period, applying artificial intelligence techniques.

  • 2020 JAFC International Award for Innovation in Roads - VIII Edition Asociación Española de la Carretera - 1 of 62

    Asphalt damage detection and segmentation through Convolutional Neural Networks.

  • 2020 Multi-Centre, Multi-Vendor & Multi-Disease Cardiac Image Segmentation Challenge MICCAI - 4 of 14

    Contribute to the effort of building generalizable models that can be applied consistently across clinical centers.

  • 2019 - 2020 Bengali.AI Handwritten Grapheme Classification Kaggle - 33 of 2059 (Top 2%)

    This challenge hopes to improve on approaches to Bengali recognition.

  • 2019 Skin Lesion Analysis Towards Melanoma Detection MICCAI - 2 of 64

    Classify dermoscopic images among nine different diagnostic categories.

  • 2018 - 2019 Humpback Whale Identification Kaggle - 128 of 2129 (Top 7%)

    Can you identify a whale by its tail?. Challenged to build an algorithm to identify individual whales in images.

  • 2018 Quick, Draw! Doodle Recognition Challenge Kaggle - 115 of 1316 (Top 9%)

    "Quick, Draw!" is a game that prompts users to draw an image depicting a certain category, such as ”banana,” “table,” etc. The game generated more than 1B drawings, of which a subset was publicly released as the basis for this competition’s training set. That subset contains 50M drawings encompassing 340 label categories. I had to build a recognizer that can effectively learn from this noisy data and perform well on a manually-labeled test set from a different distribution.


The best way to contact me is usually through email.