Jesús Cáceres Tello
Research Profile | Data Science, Urban Sustainability & Reproducible AI
🔬 Research Identity
Urban Data Science · Imbalance-Aware Modelling · Reproducible AI Systems
Jesús Cáceres-Tello is a researcher working at the intersection of urban sustainability, machine learning methodology, and open computational science.
His research focuses on the design and evaluation of predictive models under real-world constraints, particularly in environments characterised by class imbalance, temporal structure, and operational limitations.
Rather than prioritising algorithmic novelty, his work emphasises:
- Methodological rigour
- Time-aware validation
- Performance–cost trade-off analysis
- Reproducibility by design
- Open science integration
🎯 Research Mission
The core objective of my research is to develop methodologically coherent AI frameworks for urban sustainability and STEM education.
This involves:
- Evaluating models under structural imbalance
- Designing reproducible analytical pipelines
- Integrating computational efficiency into model comparison
- Linking data science with institutional decision-making
My work contributes to a broader research programme in applied data science for sustainable systems, currently developed within my doctoral studies at the Complutense University of Madrid. # 🔬 Research Areas
- 🌍 Urban environmental modelling and air quality forecasting
- ⚖️ Imbalanced learning and classification evaluation
- 🤖 Hybrid predictive architectures (Prophet–LSTM, GAT–BiLSTM)
- 📈 Performance–cost trade-off analysis
- 🧩 Open science and reproducible research infrastructures
- 🎓 AI-supported STEM education
🏗 Research Infrastructure & Open Science
All research projects are developed under a structured computational framework:
- Git-based version control
- Public repositories with DOI integration (Zenodo)
- Reproducible scripts and notebooks (R / Python / Quarto)
- Time-based validation strategies
- Transparent performance reporting
Each publication is accompanied by:
- An open repository
- Executable code
- Structured documentation
- Publicly accessible data sources
This approach ensures traceability, transparency, and methodological consistency across projects.
📚 Publications & Open Repositories
⚖️ Urban PM2.5 Imbalance Evaluation Framework
Imbalance-aware classification and performance–cost trade-off analysis (Manuscript under review, 2026)
📊 Urban PM2.5 Methodology
Reproducible methodological pipeline for urban PM2.5 time series analysis (Manuscript under review, 2026)
🌱 Behavioural and Institutional Drivers of Green Technology Adoption
TAM-based framework for sustainability transitions (Frontiers in Psychology, 2026)
🎓 Citizen Science and STEM Education with R
Reproducible AI–IoT forecasting and learning from open urban air and meteorological data (Applied Sciences, 2025)
🧠 Quantum Computing in Data Science and STEM Education
Bibliometric mapping and pedagogical analysis of quantum computing tools (Computers, 2025)
🎓 Academic Background & Professional Experience
Jesús Cáceres-Tello holds:
- Diploma in Computer Science: University of Málaga
- B.Sc. in Computer Engineering: Catholic University of Ávila
- Master’s Degree in Educational Informatics: University of Alcalá
- He is currently pursuing a Ph.D. in Statistical Studies at the Complutense University of Madrid, developing methodological frameworks for urban sustainability analytics.
His professional experience includes:
- Leadership in university digital infrastructure systems
- Participation in European Electronic Health Record interoperability projects (ISO 13606, ISO 21090)
- Development of national e-learning platforms
- Public-sector environmental technology projects at Madrid City Council
He has been teaching in higher education for over a decade and actively contributes to academic innovation initiatives.
🧑🎓 Research Profiles
You can explore my professional and academic presence across several open-science platforms. These profiles provide access to publications, collaborations, datasets, and teaching activities related to environmental informatics, STEM education, and open data research. Connect with me on:
🤝 Collaboration
I welcome collaboration in:
- Urban sustainability analytics
- Methodological AI evaluation
- Reproducible research frameworks
- Hybrid predictive systems
- AI-enhanced STEM education