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

Instrumenting Continuous Knowledge Extraction, Sharing, and Benchmarking

Keeping the pace with the faster and faster evolution of knowledge is becoming a challenge, especially for researchers and knowledge workers. We propose a vision towards a set of (possibly integrated) publicly available tools that can help on this. To this purpose, we expect tools that can improve effectiveness of knowledge extraction, storage, analysis, publishing and experimental benchmarking. This could be extremely beneficial for the entire research community across fields and interests. We describe our vision in this direction and we demonstrate its feasibility with some exemplary tools that we developed and that we shared as public resources to be used by the research community.

Model-driven Development of User Interfaces for IoT via Domain-specific Components & Patterns

This is the summary of a joint contribution with Eric Umuhoza to ICEIS 2017 on Model-driven Development of User Interfaces for IoT via Domain-specific Components & Patterns. Internet of Things technologies and applications are evolving and continuously gaining traction in all fields and environments, including homes, cities, services, industry and commercial enterprises. However, still many problems need … Continue reading Model-driven Development of User Interfaces for IoT via Domain-specific Components & Patterns

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

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