Teaching

Slides and materials from recent courses and tutorials.

Courses

Fairness, Accountability, Transparency, and Ethics in Data Processing. (2020-)

Instructors: Carlos Castillo, Catia Faria, Antoni Rubi-Puig, David Casacuberta, Ariel Guersenzvaig. Degree: Mathematical Engineering in Data Science at Universitat Pompeu Fabra. Time: 12 theory sessions x 2 hours + 12 practical sessions x 2 hours. Slides and materials »

Mining Massive Datasets (2019-)

Instructor: Carlos Castillo. Degree: Mathematical Engineering in Data Science at Universitat Pompeu Fabra. Time: 11 theory sessions x 2 hours + 12 practical sessions x 2 hours.

Topics: data preparation, near duplicate detection, association rules mining, recommender systems, outlier analysis, time series analysis, data streams. Slides and materials »

Introduction to Network Science (2018-)

Instructor: Carlos Castillo. Degree: Mathematical Engineering in Data Science at Universitat Pompeu Fabra. Time: 11 theory sessions x 2 hours + 12 practical sessions x 2 hours.

Topics: basic graph theory concepts, random networks, scale-free networks, storage of large graphs, centrality, dense sub-graphs, graph clustering, viral phenomena. Slides and materials »

Social media mining: a multi-disciplinary toolbox (2017)

Instructor: Carlos Castillo. Institution: Universidad Carlos III de Madrid. Time: 4 sessions x 3 hours.

Topics: vector space model, text indexing and search, information extraction, text summarization, supervised learning, text classification, sentiment analysis, graph models, link-based ranking, dense sub-graphs, graph partitioning, social influence model, influence maximization, mining social media, natural experiments, matching studies. Slides and materials »

Tutorials

Algorithmic Bias: from Discrimination Discovery to Fairness-Aware Data Mining (2016)

Instructors: Sara Hajian, Francesco Bonchi, and Carlos Castillo. KDD Conference, San Francisco, USA, 2016. Time: 1 sessions x 3 hours.

Topics: Context and applications; Data biases and representativeness; Methodological pitfalls and evaluation; Ethics of handling social data. Slides and materials »

Graphs and Social Networks (2016)

Instructor: Carlos Castillo. Computer Science and Informatics School (ECI), Buenos Aires, Argentina 2016.

Topics: Graph models; Link-based ranking Other centrality metrics; Social influence; Influence maximization; Dense sub-graphs; Graph partitioning; Recommending links; Recommending content; Mining social media; Observational studies. Slides and materials »

A Critical Review of Online Social Data: Limitations, Ethical Challenges, and Current Solutions (2016)

Instructors (in alphabetical order): Carlos Castillo, Fernando Diaz, Emre Kıcıman, and Alexandra Olteanu. ICWSM Conference, Cologne, Germany, 2016.

Topics: Context and applications; Data biases and representativeness; Methodological pitfalls and evaluation; Ethics of handling social data. Slides and materials »

Data Mining Technologies for Business and Society (2016)

Instructor: Stefano Leonardi. Guest: Carlos Castillo. Sapienza University of Rome, 2016.

Topics: Link Prediction; Link Prediction Using Content; Natural Experiments; Observational Studies. Slides and materials »

Algorithmic Methods of Data Science (2015)

Instructors: Aris Anagnostopoulos, Ioannis Chatzigiannakis, Carlos Castillo. Sapienza University of Rome, Fall 2015.

Topics: Vector Space Model; Clustering; K-Means Algorithm; Hierarchical Clustering; Summarization; Indexing; Text Indexing; Link-Based Ranking; Graph Evolution Models; Dense Sub-Graphs; Spectral Graph Clustering; Recommender Systems; Mining Social Media. Slides and materials »