News

• [2025.02] Our Generative Intelligence Lab is now open! 🎉🎉 We are seeking enthusiastic graduate students and undergraduate interns who are eager to join our team and contribute to our research. If you are interested in joining our lab, please complete the [application form].

Research Area

Our primary objective is to design advanced deep generative models that uncover meaningful representations 

within multi-modal information facilitating the generation of optimal and complex decision-making outcomes.

Our main research interests include but not limited to the following: 

• Application of Deep Generative Models (e.g., multi-modal diffusion models & normalizing flows, time-series analysis)

• Theory of Deep Generative Models (e.g., numerical game theory, optimal transport, mean-field theory, stochastic geometry)

• Geometric Deep Learning (e.g., Riemannian diffusion models, geometric molecule generation)

• Generative Decision-making Models (e.g., multi-modal state-space models, probabilistic decision calibration)