Adjunct professor in the bachelors "Computer Science and Artificial Intelligence" and "Big Data and Business Administration" teaching the following courses:- AI: STATISTICAL LEARNING & PREDICTION. This course introduces the theory of statistical learning, practical machine learning and deep learning algorithms. The intention behind this course is to concentrate more on the applications of the methods and less on the mathematical details, although the basis of each model will be reviewed. Thus, we study both practical algorithms for statistical inference and theoretical aspects about how to work with probabilistic models. We consider a variety of applications, including supervised/unsupervised learning, AI and Gen AI solutions.- AI APPLICATIONS IN HEALTHCARE. This course is designed to provide students with an understanding of the potential applications of artificial intelligence (AI) in the field of healthcare. Topics covered will include AI techniques such as machine learning, deep learning, natural language processing, and robotics, and how these techniques can be applied to various healthcare scenarios such as disease diagnosis, treatment planning, drug discovery, and patient monitoring. The course will also explore ethical considerations related to the use of AI in healthcare.

As part of the European AI team, my work was focused on strengthening AI Boeing’s international strategy. My responsibilities included finding new innovative AI opportunities and projects across the industry and academia, collaborating and serving as a liaison between different BR&T International Centers. From a technical point of view, we focused mainly on improving Boeing aircraft reliability while reducing costs by applying advanced analytics techniques for problems such as predictive maintenance, robotics, manufacturing processes optimization or flight autonomy.

Research on Deep Learning, Machine Learning, Neural Networks... focused on Big Data. Project carried out in cooperation with Department of Signal Theory and Communications from UC3M.

Data & Algorithms Expert in a department that combines business and technological consulting to create disruptive solutions in Artificial Intelligence, Smart Cities, Smart Homes, Smart Stores and I4.0. As a Data Scientist, the main goal was to implement Machine Learning and Deep Learning algorithms to exploit a big amount of data from every solution, thinking up new business cases.- Energy Optimization, Predictive Maintenance, Quality and Productivity Trends.- Natural Language Processing.- Computer Vision.- Social network analysis.- Machine learning and Deep Learning.- Business Development.

Development of recommender systems, search engine, customers segmentation, fraud detection and other machine learning projects. Business intelligence tasks were also carried out.- Python: Numpy, Pandas, Scikit-learn, Tensorflow, Keras, MySQLdb, PyMongo, etc.- R language.- SQL and NoSQL databases: MySQL, MongoDB, Elasticsearch.- ETL, EDA, Data Mining.- Qlik Sense.