Marco Brambilla

a49a9-ifml-logoI’m associate professor of Web Science and Software Engineering at Politecnico di Milano, Italy.

I lead the Data Science Lab at Politecnico di Milano, DEIB.

My current research interests are on Web Science, Big Data Analysis,  Social Media Analytics, and Model-driven Development.

I’m the inventor of the Interaction Flow Modeling Language (IFML) standard by the OMG, and of 2 patents on crowdsourcing and multi-domain search.

I started-up Fluxedo and WebRatio.

I currently teach:

  • Web Science (see course materials here)
  • Software Engineering
  • Advanced Software Engineering (Model-driven Engineering, see book here)

My most recent books:

 9781627057080-MDSE-Book-Brambilla-Cabot-Wimmer-modeling-small


Model Driven Engineering in Practice
(second edition)
Web Information Retrieval
Model-Driven UI Engineering
of Web and Mobile Apps with IFML

Recent Posts

News Sharing Behaviour on Twitter. A Dataset and a Pipeline

by Marco Brambilla, posted in data science

Online social media are changing the news industry and revolutionizing the traditional role of journalists and newspapers. In this scenario, investigating the behaviour of users in relationship to news sharing is relevant, as it provides means for understanding the impact of online news, their propagation within social communities, their impact on the formation of opinions, … Continue reading News Sharing Behaviour on Twitter. A Dataset and a Pipeline

A sneak peek at the European Union Ethics Guidelines for AI

by Marco Brambilla, posted in data science

A few days ago, politico.eu published a preview of the document that the European Union will issue as guidance for ethical issues related to artificial intelligence and machine learning. The document was written by the High-level Expert Group on Artificial Intelligence, appointed by the European Commission. This advanced version of the document is available online now … Continue reading A sneak peek at the European Union Ethics Guidelines for AI

Improving Topic Modeling with Knowledge Graph Embeddings

by Marco Brambilla, posted in data science

Topic modeling techniques have been applied in many scenarios in recent years, spanning textual content, as well as many different data sources. The existing researches in this field continuously try to improve the accuracy and coherence of the results. Some recent works propose new methods that capture the semantic relations between words into the topic … Continue reading Improving Topic Modeling with Knowledge Graph Embeddings

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