Oktie Hassanzadeh

Dr. Oktie Hassanzadeh is a Senior Research Scientist at IBM T.J. Watson Research Center. He is the recipient of several academic and corporate awards, including a top prize at the FinCausal-2022 Shared Task, a top prize at the Semantic Web Challenge at ISWC conference, and two best-paper awards at ESWC conferences. He has received his M.Sc. and Ph.D. degrees from the University of Toronto, where he received the IBM PhD fellowship and the Yahoo! Key Scientific Challenges awards. He is also a two-time recipient of the first prize at the Triplification Challenge at the SEMANTiCS Conference for his projects in the areas of Semantic Technologies and Linked Data.

Dr. Hassanzadeh's research interests are in the areas of data curation, information integration, and knowledge management. His current research is focused on extraction of knowledge from large and heterogeneous sources of structured and unstructured data, and integration and management of the extracted knowledge. He actively participates in Semantic Web, Data Management, and AI research communities through publications and program committee activities.

In the past, he has worked on several problems related to accurate and efficient discovery of links within and between large data repositories. In particular:

• Linking enterprise data to facilitate online exploratory data analytics and semantic data curation, in the context of the Helix project. Helix project aimed at providing a guided data exploration and analysis engine for Big Data. A highly-scalable, generic, and knowledge-drive data curation technology was developed as a part of this project.
• Linking life sciences data, in particular: 1) clinical trials data, in the context of LinkedCT and xCurator projects. 2) drug data and drug-drug-interaction (see our JBI paper).
• Linking bibliographic data in BibTeX files, as an extension of the BibBase project.

He has also worked on a framework for link discovery over relational data (the LinQuer project), and linking movie data on the web (the LinkedMDB project).

Blog posts:

• Causal Knowledge Extraction: An Evaluation using Automated Binary Causal Question Answering:
  https://www.ibm.com/blogs/research/2019/08/causal-knowledge-extraction/
  Work presented at IJCAI 2019, and system demonstrated at AAAI 2020.
• Semantic Concept Discovery Over Event Databases: https://www.ibm.com/blogs/research/2018/07/semantic-concept-discovery/ Work won the Best In Use Track Paper award at ESWC 2018:
• Automated knowledge base construction solution wins at ISWC 2017: https://www.ibm.com/blogs/research/2017/11/knowledge-base-construction-iswc-2017/

Contact

Mailing address:
1101 Kitchawan Rd Route 134 / P.O. Box 218
Yorktown Heights, NY 10598
United States

See Visitor Information for directions to the lab.
GPS coordinates: -73.806002, 41.216056.