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Computer and Information Science


Topic Model Inference for Textual Data

Textual data, such as news items, literature, and political speeches are today available in digital formats. Probabilistic topic models is a versatile class of models to analyze topic compositions in corpora. Måns Magnusson has in his thesis developed scalable and efficient methods to enable statistically correct, large-scale inference for very large corpora.

Marco Kuhlmann gets the Distinguished Teaching Award

Each year since 1990, the Union of Technology and Science Students awards the "Golden Carrot" for distinguished teaching on the programmes at the Institute of Technology. This year, the winner of this distinction is Marco Kuhlmann, Associate Professor of Computer Science at IDA, who had been nominated by the students in Computer Science and Engineering.

Prize for the best Bachelor and Master theses 2017

The computer science department together with the computer society in Sweden has for the 19th time awarded the annual prize for the best Master and Bachelor theses in 2017. The winners were among 6 thesis that were nominated this year. Alexander Ernfridsson was awarded for the Bachelor level and Tova Linder together with Ola Jigin at the Master level.




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