Dr. Eva Blomqvist

Professor

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Biography

Eva Blomqvist is a Professor at Linköping University, leading research on Artificial Intelligence (AI) and knowledge modeling. Her work focuses on the Semantic Web and the creation of smarter, more useful AI systems by developing and maintaining knowledge models and ontologies. Her research explores methods for encoding knowledge digitally so that AI systems can better understand and operate within their environments. She teaches master's programs in Computer Science Engineering and PhD courses related to knowledge modeling and Semantic Web technologies. Eva is actively involved in several national and EU-funded projects aimed at leveraging AI for sustainability, security, and e-health applications. Her notable contributions include the development of Ontology Design Patterns (ODPs) and methodologies for agile ontology engineering. Eva seeks to automate the modeling process using modern machine learning techniques to convert natural language texts into structured knowledge models. She coordinates the EU-funded project Onto-DESIDE and contributes to initiatives like Trace4Value and SwePass, focusing on data sharing and interoperability in the circular economy.

Research Interests

Experience

Professor

— Present

Linköping University • Linköping, Östergötland, Sweden

Leading research in Artificial Intelligence focused on knowledge modeling and Semantic Web.

Requirements for Linköping University

Master Program
Requirements
GPA Requirement
Required:3
IELTS
Listening
Required:5.5
Reading
Required:5.5
Writing
Required:5.5
Speaking
Required:5.5
Overall
Required:6.5
TOEFL
Listening
Required:20
Reading
Required:20
Writing
Required:20
Speaking
Required:20
Total
Required:90
Prerequisites
Bachelor's degree with a major relevant to the program At least 30 ECTS credits in mathematics/applied mathematics and/or application of mathematics
Application Checklist
  • Certificates and diplomas from previous university studies
  • Transcript of records
  • Proof of English proficiency
  • Copy of passport/ID
  • Syllabus for relevant courses
Specialization Notes

Requirements are standardized across the Faculty of Science and Engineering (Institute of Technology) for international Master's programs.