CAST Seminar: Mina Aminghafari

Join us at the CANSSI Ontario STatistics Seminars (CAST) with

Mina Aminghafari

Associate Professor
Department of Mathematics and Statistics
Faculty of Science
University of Calgary

Talk Title

Functional data model-based clustering

Abstract

Functional data analysis has attracted considerable attention in recent years, and its applications appear in physical processes, genetics, biology, meteorology, and signal processing. Many modern applications produce data best viewed as functions rather than finite-dimensional vectors because of their nature. Beyond the challenges of collecting and preprocessing such data, efficiently handling large volumes of functional observations has become an urgent concern. On one hand, functional data takes values in an infinite-dimensional space, which is challenging to handle with classical methods. On the other hand, ignoring the functionality aspect of data will lead to information loss. In this talk, we highlight model-based clustering methods, a powerful tool in machine learning for identifying subgroup-specific patterns. Specifically, we introduce new model-based clustering techniques for functional data, regardless of the Gaussian assumption. The performance of each algorithm is evaluated through simulations and real-world datasets, and the results confirm their efficiency.

Speaker Profile

Dr. Mina Aminghafari is an Associate Professor in the Department of Mathematics and Statistics at the University of Calgary. Her research lies at the intersection of high-dimensional statistics, machine learning, and applied data science, particularly on clustering theory and statistical learning and their applications in health and environmental sciences. She has contributed significantly to methodological advances in regularization techniques, co-clustering, and functional data analysis. Her work frequently bridges theory and practice, motivated by real-world challenges in biomedical diagnostics, autoimmune disease research, and environmental monitoring. 

Dr. Aminghafari actively mentors highly qualified personnel at undergraduate, graduate, and doctoral levels, focusing on their development. She also leads several interdisciplinary research projects and training programs, including co-leading the Prairie hub of STAGE (Statistical Genetics and Genetic Epidemiology) and one of the organizers of M2PI (Math to Power Industry) for the Pacific Institute of Mathematical Sciences (PIMS).