ESP Biography

MICHAEL SCHAUB, MIT PostDoc studying networks and data science

Major: Mathematics

College/Employer: MIT

Year of Graduation: 2014

Picture of Michael Schaub

Brief Biographical Sketch:

I am a Marie Skłodowska Curie Fellow with affiliations at the Institute for Data, Systems, and Society at MIT (USA), and at the Department of Engineering Science at the University of Oxford (UK). My research deals with the analysis of complex systems that can be abstracted as networks or graphs. A central methodological issue underlying my research is how one can study and integrate the multiple levels of organization which are commonplace in many systems. By combining ‘bottom-up’ dynamical models, and ‘top-down’ data-driven approaches, and using a blend of tools from control theory, dynamical systems, stochastic processes, machine learning and statistics, my goal is to shed light on key problems in this context.

I studied Electrical Engineering and Information Technology at ETH Zurich with a focus on communication systems. After a MSc in Biomedical Engineering at Imperial College (Neurotechnology stream), I moved to the Mathematics Department to obtain my PhD under the supervision of Prof. Mauricio Barahona and Prof. Sophia Yaliraki. After this I worked in Belgium, jointly at the Université catholique de Louvain and at the University of Namur, as a Postdoctoral Research Fellow. In November 2016, I moved to MIT as a Postdoctoral Research Associate. Since July 2017 I am a Marie Curie Fellow at MIT / Oxford.

Past Classes

  (Clicking a class title will bring you to the course's section of the corresponding course catalog)

M12148: Detecting fake news in Spark 2018 (Mar. 17 - 18, 2018)
This class will teach you to think critically about 'facts' presented in the news, media, and social networks like Facebook, Twitter, etc. How do you know whether the facts reported at CNN or Fox News were genuine, or 'alternative' facts? Can you find flaws in the statistical study that claims that storks deliver babies? And what is wrong with this nice looking infographic in the latest newspaper? This class will help you to spot 'fake news' in the wild.