Faculty Profile

MA Yunshan is an emerging leader in multimodal machine learning, recommendation systems, and generative AI, with impactful contributions to contrastive learning, explainable AI, and real-world applications in fashion, finance, and security.

Demonstrates methodological innovation in contrastive and generative learning, integrating multimodal data and large language models for interpretable, robust recommendation and forecasting systems; bridges theory and practice across domains such as fashion, finance, and cybersecurity; recognized for collaborative, cross-disciplinary research and real-world deployment.

Focused research areas include Advancing multimodal learning and generative models for recommendation, event forecasting, and explainable AI; developing robust, interpretable systems for bundle recommendation, fashion outfit generation, financial prediction, and rumor verification; leveraging large language models for knowledge discovery and editing.