Statistical Methods Applied to Agriculture, Life Sciences and Education

Data analysis and advisory services using complex models to identify characteristics associated with variables of interest, for example:

• Identifying risk and/or protective factors associated with diseases (personalised medicine, correlation and causation, etc.)
• Developing intelligent decision-making systems (Machine Learning and Artificial Intelligence)
• Spatio-temporal studies to detect patterns (climate change, disease mapping, early-warning detection systems, etc.)
• Studies of relevant characteristics in agronomy (experimental design, models for the optimal selection of new composts, etc.)

Data analysis to provide advice and technical assistance in biostatistics, specifically in the area of statistical design and analysis in health sciences, ecology and agronomy. Potentially interested organisations include both public and private hospitals, agricultural companies, environmental management companies and any organisation operating in a sub-sector within these fields.

Prevention and anticipation of various environmental, health-related and educational events, as well as improvements to the education system, optimisation and more efficient use of healthcare resources, and the identification of environmental factors or the soil’s physical and chemical characteristics for specific crops. These approaches can help achieve maximum performance, increase production, reduce the amount of raw material that is spoiled and reuse agricultural waste.

The research team has models that have already been validated in real-world settings and is equipped to integrate them immediately into the operational structures of companies and institutions.

• Hospitals and Health Centres (Public and Private).
• Agricultural and Biotechnology Companies.
• Environmental and Energy Management.
• Public Administration (Educational and Healthcare Planning).

Josep Xavier Barber Valles – Centre for Operations Research