张泽楷 (Zekai Zhang)

About Me [CV]

I am a third-year PhD student in EECS at the University of Michigan, advised by Prof. Qing Qu. Before that, I received my bachelor’s degree from the Department of Automation, Tsinghua University.

Research

I work on effective theory for generative models (especially diffusion models), via representation learning and simplified models. My goal is to understand, disenchant, and collaborate with generative models better.

News

• Oct 2026
  One paper on diffusion language models is on arXiv!

  Scaling and Distilling Text Embeddings for Better Diffusibility
• Aug 2026 Gratefully wrapped up my internship at TikTok Seattle (May–Aug)!
• May 2026
  One paper accepted at ICML 2026, and a Silver Reviewer award.

  Evaluating the Representation Space of Diffusion Models via Self-Supervised Principles
• Jan 2026
  One paper accepted at ICLR 2026.

  Generalization of Diffusion Models Arises with a Balanced Representation Space, with an oral talk at DeepMath.
• Oct 2025
  Two papers accepted at NeurIPS 2025.

  A Closer Look at Model Collapse: From a Generalization-to-Memorization Perspective

  Understanding Representation Dynamics of Diffusion Models via Low-Dimensional Modeling
• May 2025 Top Reviewer award at ICML 2025.