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Welcome to the Department of
Computer and Information Science

Scalable statistical methods for images and spatial data

The need for statistical analyses of images and spatial data arises in many areas. The ever-increasing sizes of these datasets pose a great computational challenge. In his thesis, Per Sidén has developed more scalable and advanced statistical methods for spatial data, with applications for brain imaging, satellite images, and robotics.

Outstanding Paper Award at ICNS'20

IDA students Hanna Gustafsson and Sofie Eskilsson were the lead authors of an article "Demonstrating ADS-B And CPDLC Attacks With Software-Defined Radio" which received the Outstanding Paper Award at the Integrated Communications, Navigation and Surveillance (ICNS'20) Conference. The work was supervised by Prof. Andrei Gurtov within the project "Automation Program II" with Trafikverket.

Contributions to Semantic Dependency Parsing

Natural language understanding is a central problem in artificial intelligence with many applications. For a computer to understand natural language, representations how words in a sentence relate to one another and how they build the sentence's meaning are commonly used. With his thesis Robin contributes to various aspects of semantic dependency parsing, the automatic analysis of these structures.

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