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

Data Science for Business Innovation. A new MOOC on Coursera

Breaking news! We just published our new MOOC “Data Science for Business Innovation” on Coursera! Our course is available for free on Coursera and is jointly offered by Politecnico di Milano and EIT Digital, as a compendium of the must-have expertise in data science for non-technical people, including executives, middle-managers to foster data-driven innovation. The … Continue reading Data Science for Business Innovation. A new MOOC on Coursera

Content-based Classification of Political Inclinations of Twitter Users

Social networks are huge continuous sources of information that can be used to analyze people’s behavior and thoughts. Our goal is to extract such information and predict political inclinations of users. In particular, we investigate the importance of syntactic features of texts written by users when they post on social media. Our hypothesis is that … Continue reading Content-based Classification of Political Inclinations of Twitter Users

News Sharing Behaviour on Twitter. A Dataset and a Pipeline

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

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