Alexander Tong

Alexander Tong is a Research Fellow at Mila and Université de Montréal (UdeM), focusing on developing computational models for proteins and cellular systems. His work integrates machine learning and generative flow networks to advance understanding in structural biology and cellular dynamics.

He contributes actively to research initiatives such as FoldFlow (protein backbone generation), FAPLM (protein language models), and TrajectoryNet (cellular dynamics modeling). His affiliations include Mila Quebec AI Institute and collaborations with organizations like BorealisAI and the KrishnaswamyLab at Yale University.

Key projects include TorchCFM (conditional flow matching library) and DynGFN (Bayesian causal discovery). Tong's research emphasizes interdisciplinary approaches, combining AI with computational biology to address challenges in protein design and systems biology.