Comparative Analysis of Public and Expert Perceptions of Electrified Vehicles in the European Union
Comparative analysis of public and expert perceptions of electrified vehicles in the EU.
andromachi-mourtzouchou
Professional Summary
PhD researcher at Universitat Politècnica de València and Scientific Project Officer at the European Commission’s
Joint Research Centre. I work on AI and social data science applied to sustainable transport — from public discourse
analysis to behavioral modeling. Background in Physics and AI, with experience in machine learning, NLP, and data analysis.
Education
PhD in Computer Science
2021-12-14
Universitat Politecnica de Valencia (UPV)
MSc in Data Science
2019-09-12
2020-06-19
Universitat Oberta de Catalunya
BSc in Physics
2012-09-14
2019-01-09
Universitat de Barcelona
PhD Student Visitor
2024-03-01
2024-03-31
University of Bristol
MSc in Space Studies (AI specialization)
2019-10-31
2020-06-30
Institut d'Estudis Espacials de Catalunya - IEEC
Interests
Artificial Intelligence
Social Data Science
Machine Learning & Deep Learning
Trustworthy AI
Sustainable Transport
Vehicle Energy Consumption
📚 My Research
My research sits at the intersection of AI, social data science, and sustainable transport. During my PhD, I developed methods to bridge laboratory and real-world vehicle performance — from energy consumption modeling and driver behavior analysis to NLP-based studies of public perception around electric vehicles. This work gave me a strong foundation in machine learning, behavioral modeling, and large-scale data analysis.
Going forward, I’m increasingly focused on social data science: understanding how public discourse, opinion dynamics, and collective behavior shape — and are shaped by — policy decisions. I’m particularly interested in applying computational methods like topic modeling, sentiment analysis, and opinion dynamics models rooted in statistical physics to study how societies engage with sustainability transitions. My goal is to produce research that informs evidence-based policy, especially within the European context.
Featured Publications
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1 min read
Human or Machine: A Novel Deep Learning Framework for Autonomous Driver Identification Based on Vehicle Trajectories
A novel deep learning framework for autonomous driver identification based on vehicle trajectories.
Follow the leader: a deep reinforcement learning framework for safe and efficient autonomous car-following
A deep reinforcement learning framework for safe and efficient autonomous car-following.
Recent Publications
(2025).
Comparative Analysis of Public and Expert Perceptions of Electrified Vehicles in the European Union.
Sci Rep.
(2025).
Human or Machine: A Novel Deep Learning Framework for Autonomous Driver Identification Based on Vehicle Trajectories.
IEEE T-ITS.
(2025).
Follow the leader: a deep reinforcement learning framework for safe and efficient autonomous car-following.
J Intell Transp Syst.
Recent & Upcoming Talks
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