University of Oregon
Dejing Dou is an Associate Professor in the Computer and Information Science Department at the University of Oregon and leads the Advanced Integration and Mining (AIM) Lab. He received his bachelor degree from Tsinghua University, China in 1996 and his Ph.D. degree from Yale University in 2004. His research areas include ontologies, data mining, data integration, biomedical and health informatics, and the Semantic Web. Dejing Dou has published more than 50 research papers, some of which appear in prestigious conferences and journals like KDD, ICDM, SDM, CIKM, ISWC, JIIS and JoDS. His KDD'07 paper was nominated for the best research paper award. He is on the Editorial Board of Journal on Data Semantics. Dejing Dou has received over $4.5 million PI or co-PI research grants from the NSF and the NIH.
Prof. Dejing Dou focuses on ontologies, data integration, data mining, biomedical and health informatics, and the Semantic Web. His research combines knowledge-driven and data-driven approaches to address three critical challenges in processing and managing real world data and knowledge: heterogeneity, reusability, and scalability.
Information resources distributed across the Internet, such as online databases, web services and Semantic Web agents, are hard to process automatically for knowledge acquisition because their data are structurally and semantically heterogeneous. Also, most current AI or machine learning systems are hard to scale to efficiently process large size of data and knowledge.
The Advanced Integration and Mining (AIM) Laboratory, directed by Prof. Dejing Dou, works on several research projects funded by the National Science Foundation and the National Institutes of Health. Recently, Prof. Dou's research has primarily focused on the following research projects:
- SKTI: Statistical Knowledge Translation and Integration
- NEMO: Neural ElectroMagnetic Ontologies
- SMASH: Semantic Mining of Activity, Social, and Health data
- OntoGrate: Ontology-based Integration for Relational Databases