Paul Pu Liang

Paul Pu Liang is an Assistant Professor at the Massachusetts Institute of Technology (MIT) Media Lab and Department of Electrical Engineering and Computer Science (EECS). He directs the Multisensory Intelligence research group, focusing on building AI systems that integrate diverse sensory inputs to enhance human-AI symbiosis. His work spans theoretical foundations, large-scale resources, and neural architectures for multisensory learning.

• Education: PhD in Machine Learning (Carnegie Mellon University), MS in Machine Learning (Carnegie Mellon), BS with University Honors in Computer Science and Neural Computation (Carnegie Mellon)
• Research Interests: Multimodal machine learning, human-AI interaction, clinical AI, generative models, and responsible deployment of AI systems
• Key Contributions: MultiBench, HEMM evaluation framework, CLIMB clinical data foundations, and multimodal transformer architectures

Recent publications emphasize multimodal foundation models, clinical applications, and socially responsible AI. His work has been recognized with multiple best paper awards and fellowships from Siebel, Facebook, and other institutions.

• Scientific Awards
  • Siebel Scholars Award
  • Waibel Presidential Fellowship
  • Facebook PhD Fellowship
  • Center for ML and Health Fellowship
  • Rising Stars in Data Science
  • Four best paper awards

Paul teaches courses on machine learning and multimodal AI at MIT and CMU. He mentors students across multiple programs including Media Arts & Sciences, EECS, and IDSS, with former advisees now at institutions like OpenAI, UC Berkeley, and Princeton.