03 / PROJECTS AND KNOWLEDGE TRANSFER

From data to decisions.

Experience with specific problems across different sectors. These examples illustrate areas of work, rather than an exhaustive list of collaborations.

AI · PROTECTING PEOPLE

01

VioGén-2

Development and validation of predictive models for repeat-offence risk assessment within the ALTEA project. Statistics and AI to support police risk assessment tools.

Related work

APPLIED RESEARCH

02

Health and wellbeing

Selected success stories include predicting musculoskeletal risk in surgeons and analysing acceptance of remote consultations. Examples from a wider track record in clinical studies, treatment evaluation and predictive tools.

Related work

RISK AND ADAPTATION

03

Marine environments

Thermal risk in aquaculture, species distributions and environmental data integration. Maps and models to inform management and adaptation.

Related work

RESOURCES AND PROCESSES

04

Agriculture and circular economy

Compost Calculator, sludge characterisation, waste valorisation, irrigation and soil zoning. Analysis to evaluate processes and resource-use options.

Related work

SUSTAINABLE MANAGEMENT

05

Golf and land management

Turf management, fertilisation and remote sensing. Evidence to inform maintenance and resource use.

Related work

QUALITY AND DEVELOPMENT

06

Food industry

Experimental design, formulation, preservation and consumer preferences. Comparing products, processes and coproduct ingredients.

Related work

04 / HUMAN-CENTRED AI

Technology supports. People decide.

Useful AI must pay attention both to model quality and to the people it affects.

My experience in risk assessment, health research and large-scale citizen surveys connects methods with social needs. I see AI as a tool to support informed decisions, with human oversight and attention to its limitations.

01

Understand

Explain what a model answers, which data it uses and what it assumes.

02

Acknowledge limits

Make uncertainty visible and assess where a tool works.

03

Care for people

Consider bias and the consequences of using the results.

04

Retain judgement

Support professional judgement and the responsibility of decision-makers.

07 / CONTACT

Your next challenge. Let's talk.

Tell me what you need to decide, what data you have or what training your team needs. Let's start with a good question.

Universidad Miguel Hernández de Elche
i-MInD Institute
03202 Elx (Spain)

Consultancy and knowledge transfer

Improve processes. Evaluate results. Make evidence-informed decisions.

Do you need to improve a process, evaluate a service or understand where AI could add value? I work with businesses and public bodies to turn that challenge into a concrete project: defining the question, analysing the data, and developing and validating a solution for your organisation.

Let's discuss your challenge