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 Politenico 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

Extracting Emerging Knowledge from Social Media

Knowledge in the world continuously evolves, and ontologies are largely incomplete.
We propose a method and a tool for discovering emerging entities by extracting them from social media.
Once instrumented by experts through very simple initialization, the method is capable of finding emerging entities; we propose a mixed syntactic + semantic method.

Spark-based Big Data Analysis of Semantic IFML Models and Web Logs for Enhanced User Behavior Analytics

I’d like to report on our demonstration paper at WWW 2017, focusing on Spark-based Big Data Analysis of  Semantic IFML Models and Web Logs  for Enhanced User Behavior Analytics. The motivation of the work is that  no approaches exist for merging web log analysis and statistics with information about the Web application structure, content and semantics. Indeed, … Continue reading Spark-based Big Data Analysis of Semantic IFML Models and Web Logs for Enhanced User Behavior Analytics

Social Media Behaviour during Live Events: the Milano Fashion Week #MFW case

We study spreading of social content  in space during live events, measuring the spreading of the event propagation in space. We build didifferent clusters of fashion brands, we characterize several features of propagation in space and we correlate them to the popularity of the brand and temporal propagation.

Data Science for Good City Life

On March 10, 2017 we hosted a seminar by Daniele Quercia in the Como Campus of Politecnico di Milano, on the topic: Good City Life Daniele Quercia leads the Social Dynamics group at Bell Labs in Cambridge (UK). He has been named one of Fortune magazine’s 2014 Data All-Stars, and spoke about “happy maps” at TED.  … Continue reading Data Science for Good City Life

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