Federico Schlüter

Federico Schlüter

Federico is granted by the National Scientific and Technical Research Council (Spanish: Consejo Nacional de Investigaciones Científicas y Técnicas, CONICET). Currently he is a full-time professor in the National Technological University of Argentina, and member of the DHARMa lab, a research team led by Facundo Bromberg. In the field of machine learning, his research is about unsupervised algorithms for learning probabilistic graphical models from digital data. Outside the world of computer science, his interests are music and philosofy.

Academic Bio



  • Ph.D. in Computer Science from November, 2014 in the National University of Central Buenos Aires. Current grant: Postdoctoral Scholarship Program in CONICET, Argentina.
  • Information systems Engineer, 2008 in the National Technological University, Facultad Regional Mendoza, Argentina.
  • Information systems analyst, 2007 in the National Technological University, Facultad Regional Mendoza, Argentina.


  •  Professional activities and Research interests

    Professional activities :

  • Worked as Teaching Assistant in the Artificial Intelligence Course. National Technological University, Facultad Regional Mendoza, 2008-2016.
  • Worked as Teaching Assistant in the Professional Habilitation Course. National Technological University, Facultad Regional Mendoza, 2008.
  • Software developer in Cubika S.A., from June 2008 to February 2009. Development of RIA applications, using Actionscript 3, FLEX, Java, javascript.
  • Software developer in CVT-Argentina from October 2007 to May 2008. Development of Java Enterprise applications, and web applications. Technologies: Hibernate, Spring Framework, Jasper reports, XStream, XML, UML, EJB3, Swing, JSP, SQL, servlets, javascript, HTML.
  • Software development in Revenue Department, Informatics Development Center, from September 2006 to September 2007. Development of web applications, frameworks development, Hibernate access to different data bases from Java, web services development, development of small projects. Technologies: MySQL, Hibernate, Jasper reports, AXIS, JAXB, XStream, XML, UML, Swing, JSP, servlets, javascript, HTML.

Research interests:

Computer science, artificial intelligence, machine learning


His scholarship is director Diego Milone, and his codirector is Roberto Santana Hermida.

His academic director is Facundo Bromberg.


Schlüter, F., Strappa Y., Bromberg F., & Milone D. H. (2017).  Blankets Joint Posterior score for learning Markov network structures . International Journal of Approximate Reasoning. https://doi.org/10.1016/j.ijar.2017.10.018,
Schlüter, F., & Bromberg F. (2014).  El enfoque IBMAP para aprendizaje de estructuras de redes de Markov. Tesis doctoral en Facultad de Ciencias Exactas - Universidad Nacional del Centro de la Provincia de Buenos Aires. Director: Facundo Bromberg. . Doctorado en Ciencias de la Computación (PhD in Computer Science), 138.
Schlüter, F., Bromberg F., & Edera A. (2014).  The IBMAP approach for Markov network structure learning. Annals of Mathematics and Artificial Intelligence. 72(3), 197--223.
Edera, A., Schlüter F., & Bromberg F. (2014).  Learning Markov networks networks with context-specific independences.. International Journal on Artificial Intelligence Tools. 23(06), 
Edera, A.., Schlüter F.., & Bromberg F.. (2013).  Learning Markov networks with context-specific independences. IEEE 25th International Conference on Tools with Artificial Intelligence (ICTAI).
Schlüter, F. (2012).  A survey on independence-based Markov networks learning. Artificial Intelligence Review. 42(4), 1093.
Bromberg, F.., Schlüter F.., & Edera A.. (2011).  Independence-based MAP for Markov networks structure discovery. 23rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI).
Schlüter, F., Bromberg F., & Pérez D. S. (2010).  Speeding up the execution of a large number of statistical tests of independence. Proceedings of ASAI 2010, Argentinean Symposioum of Artificial Intelligence.
Bromberg, F., & Schlüter F. (2009).  Variante de grow shrink para mejorar la calidad de markov blankets. XXXV Latin American Informatics Conference (CLEI), Pelotas, Brasil.