Ricardo Bernal Torres
@ricardobernaltorres
I build applied AI systems for predictive modeling, synthetic data, and intelligent decision support.
SpainWhat I'm looking for
At Nfq Advisory, I develop AI solutions for nuclear emergency management, generating physics-informed synthetic data and training models for scenario classification and decision support.
I've built a convolutional autoencoder for anomaly detection in gamma spectrometry data and integrated LLMs to generate automated, explainable incident reports. Previously at Dawako Medtech, I independently developed a deep-learning pipeline for ultrasound muscle segmentation and a sarcopenia prediction model.
My work also includes financial data control and reporting at CIMD Intermoney, alongside research collaborations on gender and health data using clustering, PCA, data cleaning, and quantitative analysis.
With master's training in Big Data and Neuromarketing & Consumer Behavior, plus a background in Social and Cultural Anthropology, I'm drawn to human-centered AI, cognition, human behavior, MLOps, cloud-based AI architectures, and applied AI research.
Experience
Work history, roles, and key accomplishments
National Security Project - Nuclear Emergency Management:
- Generated synthetic data using Physics-Informed Neural Networks (PINNs) while preserving physical behavior and system constraints.
- Designed and trained machine learning models for emergency scenario classification and decision support.
- Developed a convolutional autoencoder for anomaly detection in gamma spectrometry data.
- Integr
- Banking Data Control.
- Data cleaning and reporting to the Bank of Spain.
Data Analyst - Research Collaboration
Feb 2024 - Mar 2025 (1 year 1 month)
- Collaborated on academic research related to gender and health data.
- Cleaned and structured datasets for quantitative analysis.
- Supported the identification of key indicators and patterns for publication.
- Development of an unsupervised predictive model (Clustering).
- Contributed as a data consultant alongside the core research team.
- Developed a Deep Learning pipeline for muscle segmentation using ultrasound images.
- Built a classification model for sarcopenia prediction.
- Designed a proposal for a web interface to visualize inference results.
- Conducted the project independently in collaboration with a medical tech company.
- Development of Personalized Marketing Strategies.
- Data Analysis and Interpretation.
- Visualization of Results and Insights
- Data Acquisition and Cleaning.
- Interpretation and Visualization.
- Proposals for Stakeholders.
Education
Degrees, certifications, and relevant coursework
Universidad Complutense de Madrid
Master's degree, Big Data
2023 - 2024
Note: 9.5
- SQL
- No SQL (Mongodb)
- Python
- Machine Learning
- Minería de Datos
- Deep Learning
- Tableau
- Spark
- Hadoop
Universidad Complutense de Madrid
Master, Neuromarketing & Consumer Behavior
2022 - 2023
- Tools used: Eye Tracking, Facial Coding, GSR, and EEG.
- Neuroscientific, qualitative, and quantitative research.
- Data analysis and interpretation.
Universidad de Negocios de Copenhague
An Introduction to Consumer Neuroscience and Neuromarketing, Neuromarketing and consumer behaviour
2022 - 2022
Universidad Complutense de Madrid
Grado, Antropología Social y Cultural
2015 - 2020
Tech stack
Software and tools used professionally
Availability
Location
SpainAuthorized to work in
Job categories
Skills
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