 Dr. Maximilian Dylla, of Neu-Ulm, has won one of the two Dissertation Awards granted by the division for Databases and Information Systems of the
Dr. Maximilian Dylla, of Neu-Ulm, has won one of the two Dissertation Awards granted by the division for Databases and Information Systems of the  German Informatics Society, GI (“Gesellschaft für Informatik”). GI awards the best PhD theses of this research field every two years in the context of the
German Informatics Society, GI (“Gesellschaft für Informatik”). GI awards the best PhD theses of this research field every two years in the context of the  Conference for Business, Technology and Web (BTW), which was held in Hamburg in February 2015 this time.
Conference for Business, Technology and Web (BTW), which was held in Hamburg in February 2015 this time.
 In his PhD thesis, Maximilian Dylla elaborates on a new, unified approach for learning and query processing under a probabilistic and temporal database model. The latter is technically quite challenging as it combines various aspects from database research, probability theory, and machine learning. Dr. Dylla's thesis makes a number of key contributions in this field by providing a unified data model for both probabilistic and temporal relational data. Furthermore, a novel algorithm for top-k query evaluation under this data model was developed by him. This algorithm in particular avoids full evaluation of probabilistic queries against the underlying database and is yet able to return the k most probable query answers in an exact way.
In his PhD thesis, Maximilian Dylla elaborates on a new, unified approach for learning and query processing under a probabilistic and temporal database model. The latter is technically quite challenging as it combines various aspects from database research, probability theory, and machine learning. Dr. Dylla's thesis makes a number of key contributions in this field by providing a unified data model for both probabilistic and temporal relational data. Furthermore, a novel algorithm for top-k query evaluation under this data model was developed by him. This algorithm in particular avoids full evaluation of probabilistic queries against the underlying database and is yet able to return the k most probable query answers in an exact way.
Dr. Dylla studied Computer Science at the  Karlsruhe Institute of Technology (KIT), at the
Karlsruhe Institute of Technology (KIT), at the  University of Gothenborg (Sweden) and at
University of Gothenborg (Sweden) and at  Saarland University. He obtained his Bachelor degree from the University of Karlsruhe in 2007, a Master degree from the University of Gothenborg in 2009, and was promoted with a doctoral degree at Saarland University and the Max-Planck-Institute for Informatics (MPI-Inf) in Saarbrücken in 2014. Dr. Dylla is currently working as a PostDoc for
Saarland University. He obtained his Bachelor degree from the University of Karlsruhe in 2007, a Master degree from the University of Gothenborg in 2009, and was promoted with a doctoral degree at Saarland University and the Max-Planck-Institute for Informatics (MPI-Inf) in Saarbrücken in 2014. Dr. Dylla is currently working as a PostDoc for  Google in Paris.
Google in Paris.
The PhD thesis was jointly supervised by  Prof. Dr. Gerhard Weikum (MPI-Inf) and
Prof. Dr. Gerhard Weikum (MPI-Inf) and  Prof. Dr. Martin Theobald (Ulm University). Finally, we would like to thank
Prof. Dr. Martin Theobald (Ulm University). Finally, we would like to thank  Prof. Dr. Dan Suciu (University of Washington) who served as an external reviewer.
Prof. Dr. Dan Suciu (University of Washington) who served as an external reviewer.

