Osmar Zaïane focuses on pattern discovery and information extraction from large databases, also known as data mining.

Augmented decision-making

Osmar Zaïane focuses on pattern discovery and information extraction from large databases, also known as data mining. His work involves data mining from the disparate heterogeneous data sources, such as on the Internet, as well as the analysis of complex information networks, also known as social network analysis. Specific research projects include the development of tools for data analytics such as Meerkat, a tool for analysing changes over time in a network of entities. Other of Osmar’s research projects relate to data mining in health informatics and the development of tools for document categorization and decision support systems. He focuses on building applications that can improve decision making in fields from business to medicine, allowing decisions to be based on data and data analysis. Through the application of machine learning and methods of knowledge discovery, he devises ways to personalize applications, automate processes and improve upon current data science practices.

Osmar is a Canada CIFAR AI Chair and Fellow at Amii and a Professor at the University of Alberta in the Department of Computing Science. He has received best paper awards conferences such as the International Conference on Intelligence Text Processing and Computational Linguistics, the International Conference on Database and Expert Systems Applications, and the IEEE International Conferences on Digital Economy and of Hybrid Information Systems. Osmar has published more than 300 papers in refereed international conferences and journals and has delivered invited talks at conferences such as the International Conference on Educational Data Mining and the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Osmar has been the academic supervisor of more than 90 Master’s and Doctoral students as well as Postdoctoral Fellows.