
Position
Assistant Professor, Department of Medicine, McGill University
Research Interests
Our lab focuses on studying cell dynamics in various biological processes in many diseases (e.g., developmental disorder, pulmonary diseases, cancers). Decoding cell dynamics is essential for understanding the pathogenesis of diseases and finding novel therapeutics. The existence of enormous heterogeneity in those diseases makes it challenging to decipher the unknown.
The advancing single-cell technologies that profile individual cell states provide unprecedented opportunities to tackle this problem, which could drive biological discoveries and medical innovations in various fields (such as developmental and cancer biology). However, the single-cell data presents numerous new challenges in developing computational models that bridge the biomedical data and potential discoveries.
Our primary research is to develop machine learning approaches (particularly probabilistic graphical models) to jointly analyze, model, and visualize single-cell (and/or bulk) omics data (preferably longitudinal or spatial). Such computational models will be used to help us derive a deeper understanding of the cell dynamics in different biological systems, which will eventually benefit the public health with machine-learning driven new diagnostic and therapeutic strategies.
In the News

AI Tool Identifies Aggressive Cancer Cells
A new AI tool developed by Jun Ding identifies the most aggressive cancer cells and predicts patient outcomes.

AI is Transforming Drug Discovery – Jun Ding Featured by BBC
Work by Jun Ding featured by the BBC highlights how AI is accelerating treatment discovery for complex diseases

CIHR Project Grant Results – Fall 2025
Congratulations to all RESP members who were funded in the Fall 2025 CIHR Project Grant Competition!

Jun Ding’s AI4Health Works Featured by Anaconda, a Global AI Leader
Jun Ding and his team are transforming drug discovery with AI, earning global recognition from Anaconda for their AI4Health work

AI Tool DOLPHIN Uncovers Hidden Disease Markers Inside Single Cells
Jun Ding and team have developed DOLPHIN, an AI tool that goes beyond gene-level analysis to detect overlooked disease markers

UNAGI: Simulating Disease to Discover New Treatments with AI
Jun Ding and his team develop UNAGI, a deep generative AI tool to decode cellular dynamics and model disease

2025-2026 FRQS Salary Awards
Congratulations to Jun Ding, Bryan Ross, and Nicole Ezer for their FRQS salary award!

New AI Tool Reveals Hidden Clues to Disease Outcomes
RAMEN is a novel AI tool that uncovers hidden links between symptoms and outcomes in diseases like COVID-19, COPD, and sepsis – advancing precision medicine.

CIHR Project Grant Results – Fall 2024
Congratulations to all RESP members who were funded in the Fall 2024 CIHR Project Grant Competition!
Contact Information
Meakins-Christie Laboratories
RI-MUHC, Block E
Office EM3.2212
1001 Decarie Blvd.
Montreal QC H4A 3J1
Canada
Tel: 514-934-1934
E-Mail: jun.ding [at] mcgill.ca
Education & Training
MSc (Electrical Engineering), University of Science and Technology of China, 2010
PhD (Computer Science), University of Central Florida, 2016
PDF (Computational Biology), Carnegie Mellon University, 2020