唐帆(Fan Tang)

Making pixels dance and GPUs scream for a living.

I am a Professor at the School of Computer and Communication Engineering, University of Science and Technology Beijing (USTB). Before joining USTB in September 2026, I was an Associate Professor at the Institute of Computing Technology, Chinese Academy of Sciences (ICT, CAS) from 2022 to 2026, conducting research on image and video generation technology. Earlier, I was a faculty member at the School of Artificial Intelligence, Jilin University.

I received my Ph.D. in 2019 from the National Laboratory of Pattern Recognition (NLPR) at the Institute of Automation, CAS (CASIA), within the Multimedia Computing Group, under the supervision of Prof. Baogang Hu and Prof. Weiming Dong. During my doctoral studies, I spent one year as a visiting researcher at the University of Konstanz, Germany, collaborating with Prof. Oliver Deussen.

My current research primarily focuses on 2D digital humans, image editing, and digital art generation.

🔥News

  • 🎉Breaking the Uniformity Trap: Scaling Video Diffusion Model via SplitMoE was accepted to NeurIPS 2026 as a Spotlight. Congratulations to Yu Xu!
  • 🧑‍⚖️Serve as Pacific Graphics (PG) 2026 TPC member.
  • 🎉Joined the School of Computer and Communication Engineering, University of Science and Technology Beijing (USTB) as a Professor.
  • 🎉Beyond Pixels: Visual Metaphor Transfer via Schema-Driven Agentic Reasoning was accepted to SIGGRAPH Asia 2026. Congratulations to Yu Xu!
  • 🧑‍⚖️Serve as SIGGRAPH Asia 2026 TPC member.
  • 🎉4 papers accepted to CVPR 2026: 2 in the main track and 2 in the Findings track.
  • 🧑‍⚖️Serve as SIGGRAPH Asia 2025 TPC member.

🎨Representative Works

📢Join Us

I am always looking for highly motivated students or interns who are interested in 2D AIGC.

  • 🎯 Research Directions: We focus on the intersection of computer vision and computer graphics, powered by modern agents.
  • 💻 Required Skills: A solid foundation in mathematics (linear algebra/optimization), proficiency in Python and PyTorch for deep learning research, and a strong capability for reading and writing top-tier academic papers in English.
  • ⭐ Desired Traits: We value candidates who are highly self-motivated and intellectually curious, possessing the grit and persistence required to navigate the long-term challenges of high-level academic research.
  • 📧 How to Apply: Please send your CV, transcripts, and representative research works to tfan.108@gmail.com with an email subject formatted as “Your Name - University”.