Jun Ding

Affiliate Member

Assistant professor, McGill University, Department of Medicine

Research Topics

Computational Biology

Medical Machine Learning

Representation Learning

Website

Google Scholar

Biography

Jun Ding is an assistant professor in the Department of Medicine of the Faculty of Medicine and Health Sciences at McGill University.

Alongside his team, he is dedicated to employing machine learning techniques to decipher the complex dynamics of cells in various diseases, such as developmental disorders, pulmonary diseases and cancers. The diverse and intricate nature of these conditions necessitates innovative approaches, prompting the use of state-of-the-art single-cell technologies to meticulously profile individual cell states. The result is a rich source of data for our machine learning models.

These technologies present unprecedented opportunities to advance understanding, particularly in fields like developmental and cancer biology. However, the challenge is to develop computational models capable of linking this intricate biomedical data to potential discoveries.

Ding’s primary focus lies in the development and refinement of machine learning methodologies, especially probabilistic graphical models, to effectively analyze, model and visualize both single-cell and bulk omics data, often featuring longitudinal or spatial dimensions. The goal is to harness these advanced machine learning techniques to deepen the comprehension of cellular dynamics, and so develop groundbreaking diagnostic and therapeutic strategies that can significantly benefit public health.