Research group

Machine Learning and Information Management Lab

There are many different aspects to BIG DATA whether challenging Veracity or Variety they all require sophisticated statistical analysis, provided by machine learning. While Volume and Velocity are impossible without efficient technical solutions. Our research interests are spread among these directions. Most of our experience comes from the field of Information Retrieval and Databases.

Main research projects

Theoretical Machine Learning (ML)

Tree models, sequence analysis, ensembles, and GPU enabled ML

Search Engines (SE) and Information Retrieval (IR)

ML for Ranking, SE User Behaviour Analysis, SE performance, SE evaluation and Storage and processing of scientific and graph data

Information Management

Stream processing, declarative computation in BD environment. Efficient storage and index structures, e.g column-oriented DB. Optimization and execution of declarative queries and workflows. The holistic application, optimization, and tuning. Data quality. Consistency and high reliability.

Beside the research projects, we deliver special courses:

Students interested in research problems in the areas of our interest are welcome to join our lab. The best way to learn more about our research is to take our courses or attend our open seminars. New projects are launched regularly, sometimes it is also possible to join an ongoing project or extend its scope. Please contact the project leader for information on a specific project.

All students willing to join our projects must be skilled in either statistics or programming, preferably in both. The successful candidates will be invited to join one of the projects as a regular team member.


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