This is a multidisciplinary group with a strong background in applied and methodological Data Science research. Our research is fundamentally developed in statistical processes and is especially powerful in both data modeling and experimental designs, including active learning.
These are the main research lines:
- Experimental designs
- Statistical modeling
- Active learning
- Natural language processing and Sentiment analysis
- Complex networks: data mining and dynamics
- Optimization of energy-efficient engineering solutions
- Fractional Integration time series and Long Memory Processes
- Optimization algorithms and machine learning techniques
- Psychometry
Gamero Salinas, Juan Carlos
PhD
Lines of research:
- Experimental design
- Statistical modelling
- Thermal comfort & energy savings
López Fidalgo, Jesús
Lines of research:
- Experimental design
- Statistical modeling
- Active learning
Miranda Galcerán, Montserrat
PhD
Lines of research:
- Complex systems
- Logistics and operations research
- Applied Physics
Lines of research:
- Times series
- Fractional Integration
- Long Memory Processes
Rodríguez Carreño, Ignacio
PhD
Personal website
Lines of research:
- Signal processing
- Econometrics
- Optimization algorithms and machine learning techniques
Viles Díez, Elisabeth
PhD
Lines of research:
- Improvement of organisations processes using Statiscal models and Statiscal learning
Aznárez Sanado, Maite
PhD
Lines of research:
- Experimental design
- Functional magnetic resonance imaging
- Data analysis
- Psychometry
De la Calle Arroyo, Carlos
PhD
Lines from research:
- Experimental designs
- Statistical modeling
- Optimization algorithms and machine learning techniques
Leiva Murillo, Jose M.
PhD
Research lines:
- Advanced portfolio optimization techniques
- Advanced pricing methods based on Machine Learning and Reinforcement Learning
