ABOUT ME

My main interests lie within the field of applied data analysis, specially on social-political behavior.

I am currently collaborating in:

  • REPBIAS (“The sources of representation bias: An approach from political and economic history”) research project (UOC/IPERG/UAB), creating and evaluating models that allow predicting the consequences of manipulating electoral institutions in controlled environments.
  • The GEOCONDAH research group (UOC/ICIP) in the “Nuclear deterrence, education and transformational change project” of the Grup d’estudi en Geopolítica, Conflicte i Drets Humans (GEOCONDAH) research group in the Law and Political Science studies (UOC).The aim of the project is to analyze the current political discourse with reference to the return of the dynamics of nuclear deterrence at the root of the war in Ukraine in order to see the role of higher education in the discourse promoting Peace.
  • AGEAI: “Ageism in AI: new forms of age discrimination and exclusion in the era of algorithms and artificial intelligence” project within the CNSC research group at the IN3 institute of the University. The project aims to develop automated procedures for detecting and analyzing age biases in images generated by generative AI systems.


If you wonder about my background, I attented a Political and Administration Sciences (Comparative Politics mention) degree at Universitat de Barcelona (2019) and a Data Analyst for political analysis and public management (Research methodolgy and quantitative methods, Universitat de Barcelona, 2021) postdegree


Below you will find some of my acquired skills on my journey:

  • Data analysis (performance comparison, trends & correlations) and visualization.
  • Statistics (Descriptive, Inferential, Hypothesis Testing, Q-Tests, T-Tests)
  • Feature Engineering, feature Selection and Dimensionality Reduction. Model explanation, Cross Validation and Model Evaluation.
  • Machine learning (Supervised & unsupervised):
    • Regression models (linear, polynomial & logistic), Random Forest/ XGBoost, Clustering (K-means), PCA, Classification Models.
  • Neural Networks (model development & evaluation)
  • Natural Language Processing (TF-IDF, LDA, Word2Vec, T-sNE, Sentiment Analysis)
  • Generative AI: LLM implementations (RAG), Image and video.
  • Time Series Forecasting (Prophet / LSTM)
  • Deployment; dashboard & data apps.
  • Big data (Apache Spark, SparkML, Apache Hadoop, SparkSQL)
  • Data mining (APIs, Open Data, Scientific Data, Webscraping-Crawling)

This website is all made within RStudio and Quarto ecosystem.

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