Biography

José Ángel Martín Baos is an Assistant Professor (PhD) at the Escuela Superior de Informática of the University of Castilla-La Mancha. He obtained his PhD in Advanced Computer Technologies from the University of Castilla-La Mancha in 2023. There, he graduated with honors on both a BSc. in computer science in the year 2018, and a MSc. in computer science in the year 2019.

Since 2016, José Ángel has been working as a researcher in the MAT (Modelos y Algoritmos en Sistemas de Transportes) research group at the University of Castilla-La Mancha. His research focuses on the use of machine learning models and artificial intelligence for solving optimization problems in the field of transportation. Specifically, he has worked on the application of machine learning models for transport demand modeling.

Interests
  • Machine Learning
  • Artificial Intelligence
  • Optimization
  • Discrete Choice Models
Education

  • PhD in Computer Science, 2019-2023

    University of Castilla-La Mancha

  • MSc in Computer Science, 2019

    University of Castilla-La Mancha

  • BSc in Computer Science, 2018

    University of Castilla-La Mancha

Hello, my name is José Ángel

I’m a researcher at the University of Castilla-La Mancha 🏫

About me

Most recent publications

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Recent Posts

On July 7th, I defended my Ph.D. thesis in Advanced Computer Technologies
On Friday, July 7, 2023, I successfully defended my doctoral thesis titled ‘Machine learning methods applied to transport demand modelling,’ under the supervision of Professors Ricardo García Ródenas and Luis Rodríguez Benítez.
Last updated on Sep 11, 2023 3 min read
On July 7th, I defended my Ph.D. thesis in Advanced Computer Technologies
A webpage to monitor the propagation of COVID-19 disease
The MAT research group from the University of Castilla-La Mancha is developing a website to visualise and monitor the progress of COVID-19 disease in each country and autonomous community in the case of Spain.
Last updated on Sep 11, 2023 2 min read
A webpage to monitor the propagation of COVID-19 disease
Sysorm 2019
This week I have attended the 2nd Spanish Young Statisticians and Operational Researchers Meeting (SYSORM) where I have presented a platform for monitoring air pollution an road traffic in cities.
Last updated on Sep 11, 2023 1 min read
Sysorm 2019

Most recent publications

A prediction and behavioural analysis of machine learning methods for modelling travel mode choice
The emergence of a variety of Machine Learning (ML) approaches for travel mode choice prediction poses an interesting question to …
Code DOI URL ArXiv preprint
A prediction and behavioural analysis of machine learning methods for modelling travel mode choice
A comparative study of machine learning, deep neural networks and random utility maximization models for travel mode choice modelling
Traditionally, Random Utility Maximization (RUM) models have been widely applied to travel mode choice modelling. Currently, Machine …
DOI URL
A comparative study of machine learning, deep neural networks and random utility maximization models for travel mode choice modelling
IoT based monitoring of air quality and traffic using regression analysis
Dynamic traffic management (DTM) systems are used to reduce the negative externalities of traffic congestion, such as air pollution in …
PDF DOI URL
IoT based monitoring of air quality and traffic using regression analysis
A Python package for performing penalized maximum likelihood estimation of conditional logit models using Kernel Logistic Regression
In the last few years, the success of Machine Learning (ML) algorithms has led to the extension of their applications to areas such as …
DOI URL
A Python package for performing penalized maximum likelihood estimation of conditional logit models using Kernel Logistic Regression
Revisiting kernel logistic regression under the random utility models perspective. An interpretable machine-learning approach
The success of machine-learning methods is spreading their use to many different fields. This paper analyses one of these methods, the …
PDF DOI
Revisiting kernel logistic regression under the random utility models perspective. An interpretable machine-learning approach
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Recent & Upcoming Talks

Projects

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All Transport
Meeting Artificial Intelligence and Machine Learning for Rail Passenger Service Planning under Competition

Meeting Artificial Intelligence and Machine Learning for Rail Passenger Service Planning under Competition

PID2020-112967GB-C32

Project page
Robustez, eficiencia y recuperación de sistemas de transporte público

Robustez, eficiencia y recuperación de sistemas de transporte público

TRA2016-76914-C3

Project page

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