Academic profile · University of Jaén
Lecturer in Computer Science · PhD in Advanced Computing, Energy and Plasmas
Human Mobility · Geospatial Machine Learning · Multi-label Learning
About
My work develops interpretable, transferable methods for learning from mobile-network and geolocated digital traces.
I am a lecturer in Computer Science at the University of Jaén’s Escuela Politécnica Superior de Linares and a researcher working at the intersection of human mobility, geospatial data science and machine learning.
I earned my PhD in Advanced Computing, Energy and Plasmas at the University of Córdoba. My thesis, “Identification of population patterns using advanced machine learning techniques applied to mobile phone and geolocation data,” was defended on 4 June 2026 and awarded Sobresaliente cum laude with International Mention.
During an international research stay with the Digital Geography Lab at the University of Helsinki, I collaborated on methods for sensing cross-border labour mobility from geolocated social media. My current research studies mobility modelling, digital traces, spatial machine learning, multi-label classification and urban analytics.
Experience
Academic and technical experience spanning machine learning research, software engineering and teaching in computer science.
September 2025–present
Linares, Spain · Lecturer in the Department of Computer Science at the Escuela Politécnica Superior de Linares, teaching programming, databases, intelligent systems, mobile and distributed systems, and introductory computing across engineering degrees.
2025
Córdoba, Spain · Three-month technical appointment supporting the multi-label learning project PID2022-141869NB-I00.
2021–2025
Córdoba, Spain · Predoctoral fellowship FPU-UCO-2020 focused on population-pattern identification from mobile phone and geolocation data using advanced machine learning.
March–August 2020
Málaga, Spain · Software development and testing with C#, Visual Studio and 5G technologies.
October 2018–June 2019
Córdoba, Spain · Research training in Python, machine learning and classification.
Education
A computing background developed through software engineering, telematics and advanced doctoral research.
2021–2026
University of Córdoba
Sobresaliente cum laude · International Mention
Identification of population patterns using advanced machine learning techniques applied to mobile phone and geolocation data
2020
University of Málaga
2015–2019
University of Córdoba
Featured publication
Multi-label learning reveals concurrent urban functions that single-label clustering hides.
A supervised multi-label framework that identifies concurrent urban functions from mobile-network activity and generalises across Milan and Trento.
Selected research
The publication record spans population-pattern identification, cross-border mobility and locally adaptive classification.
A transferable machine-learning framework for detecting cross-border commuting from geolocated social-media traces across three European regions.
An evolutionary approach that deliberately modifies training labels to improve multi-label classification across diverse datasets and models.
Supervised land-use classification from call detail records in an alpine setting, testing generalisation beyond dense metropolitan areas.
A supervised alternative to classical clustering for identifying meaningful places from call detail records.
Completed doctorate
The thesis develops supervised and multi-label methods for identifying meaningful places and mobility patterns from mobile phone and geolocated social-network data.
Contact
The most reliable way to reach me is through my University of Jaén address.
mmhurtad@ujaen.es