- Data Mining
- Machine Learning
- Social Network Analysis
- +۱۴ مورد دیگر
Osmar Zaiane is a Professor in the Department of Computing Science at the University of Alberta's Faculty of Science. With over 20 years of service at the university, he has established himself as a leading researcher in data mining and machine learning with applications across multiple domains. His educational background includes a Ph.D. in Computer Science from Simon Fraser University (1999), a Master's in Computer Science from Laval University (1992), a Master's in Electronics from Institut National des Sciences et Techniques Nucléaires and Paris XI University (1989), and a Bachelor's in Computing Science from Institut Supérieur de Gestion, Université de Tunis (1988). Zaiane's research focuses on discovering patterns in large complex datasets with practical applications. His primary research interests include data mining, machine learning, social network analysis (particularly community mining and link prediction), and precision health applications. He has made significant contributions to associative classifiers, class imbalance learning, explainable AI, and educational data mining. His work spans multiple application domains including healthcare (particularly for Alzheimer's disease prediction, diabetic retinopathy grading, and lung cancer detection), social media analysis, and natural language processing. His publication record shows a strong focus on medical AI applications, with numerous recent papers on medical image segmentation, brain network analysis, and diagnostic systems. His work increasingly integrates large language models and transformer architectures with traditional machine learning approaches. Best Paper Award at IEEE/ACM Int. Conf. on Advances in Social Network Analysis and Mining (2023) Best Paper Award at International Symposium on Foundations and Applications of Big Data Analytics (2022) Best Paper Award at International AAAI Conference on Web and Social Media (2019) Best Paper Award at 29th International Conference on Database and Expert Systems Applications (DEXA) (2018) Zaiane has supervised over 80 graduate students during his career at the University of Alberta. His research has been supported by numerous grants, particularly in the areas of precision health and educational data mining. He maintains an active research lab focusing on applied machine learning with strong industry and healthcare partnerships. His current work explores the intersection of traditional machine learning techniques with emerging large language models and vision-language models for healthcare applications.