Tutored Projects, Teaching Innovation Projects,...

Here you will find the final projects I have tutored:

Also, you will find the Teaching Innovation Projects I have been involved in.

Tutored Final Masters Projects

Project #1

Title: “Ordinal classification techniques for time series”

Author: Rafael Ayllón Gavilán
Academic Year: 2021/2022
Qualification: 10.0 (with High Honors)


Tutored Final Degree Projects

Project #9

Title: “Kickboxing tourney: aplicación web para la administración de competiciones de kickboxing”

Author: Antonio Francisco Espejo Santofimia
Academic Year: 2023/2024
Qualification: 9.5 (outstanding)


Project #8

Title: “Integration of CSSVC algorithm and regression algorithm wrapper in ORCA-Python”

Author: Manuel Jesús Cabrera Delgado
Academic Year: 2022/2023
Qualification: 10.0 (with High Honors)


Project #7

Title: “Stealthy Spy, a platform game for Android devices”

Author: Alberto Adamuz Priego
Academic Year: 2022/2023
Qualification: 9.0 (outstanding)


Project #6

Title: “GoRegister: web application for the control and management of attendance at events”

Author: Antonio Ramírez Pareja
Academic Year: 2021/2022
Qualification: 9.5 (outstanding)


Project #5

Title: “OrdClass: web application for the analysis of ordinal classification problems”

Author: Jesús Bueno Ruiz
Academic Year: 2021/2022
Qualification: 9 (outstanding)


Project #4

Title: “Artificial Neural Network Training Algorithms for the Orca-Python Library”

Author: Adrián López Ortíz
Academic Year: 2020/2021
Qualification: 9.5 (outstanding)


Project #3

Title: “Recovering Time Series: application to Wave Height Problems”

Author: Victoriano Pedrajas Fernández
Academic Year: 2019/2020
Qualification: 10.0 (with High Honors)


Project #2

Title: “Machine learning applied to the survival analysis in liver transplantation”

Author: Pedro José Villalón Vaquero
Academic Year: 2018/2019
Qualification: 10.0 (with High Honors)


Project #1

Title: “Development of a Python framework for time series prediction using machine learning algorithms.”

Author: Miguel Díaz Lozano
Academic Year: 2017/2018
Qualification: 10.0 (with High Honors)


Teaching Innovation Projects

Introducing fairness, accountability, transparency and ethics (FATE) in artificial intelligence training with an emphasis on a gender perspective (2022/2023)

Hackathon on Machine Learning applied to Life Sciences (2020/2021)

Combined use of the Flipped Classroom pedagogical model, the collaborative learning technique collaborative learning technique Jigsaw and gamification through applications such as Kahoot! or Plickers (2019/2020)

Raising the profile of data science professionals through dynamic, competition-based and a working group on machine learning (2018/2019)