Budak Arpinar

Blurred image of the arch used as background for stylistic purposes.
Associate Professor, School of Computing

Dr. Arpinar is an Associate Professor of Computer Science at the University of Georgia and a member of the Large Scale Distributed Information Systems (LSDIS) Lab. He earned his BSc, MSc, and PhD degrees in Computer Engineering from the Middle East Technical University. His research has long focused on advancing the capabilities of information systems, with contributions spanning semantic web technologies, information fusion, and collective intelligence. He has also played a key role in developing adaptable workflow technologies and semantic-based methods for improved information integration and search experiences on the web.

Dr. Arpinar’s work encompasses a broad range of interconnected fields including human brain–inspired AI, neuro-symbolic computing, semantic web and knowledge graphs, and social computing. His research has been supported by organizations such as the National Science Foundation and the University of Georgia Research Foundation, resulting in over seventy publications and several research prototypes and products.

Education:

PhD    1998    Middle East Technical University (METU), Department of Computer Engineering
MSc    1993    Middle East Technical University (METU), Department of Computer Engineering
BSc    1991    Middle East Technical University (METU), Department of Computer Engineering

Research Interests:
  • Brain-inspired and neuro-symbolic AI / knowledge-infused learning
  • Foundation models and time-series forecasting
  • Semantic Web and knowledge graphs
  • Social computing, social media analytics, and collective intelligence
  • Bio/health informatics
  • Databases and distributed information systems
Of note:

My current research interests include semantic web, crowdsourcing and collective intelligence, information fusion, and biomedical informatics. My research focuses on developing new semantic-based techniques for providing better information integration, search, and knowledge discovery experiences for web users. This research direction is critical for building the next generation of web, called semantic web.