Yi Zhou (周奕)

Research Scientist at ByteDance Seed

About Me

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I am currently working on Large Language Models at ByteDance Seed, with a focus on scaling, optimization, and post-training.

My previous work also spans AI for Science. I established the cryo-EM research team at ByteDance, where our first work, CryoSTAR, was accepted by Nature Methods. I led the development of SeedFold, the first model to outperform AlphaFold3.

I received my Master's degree from Fudan NLP (2021) under Prof. Xiaoqing Zheng. I visited UCLA in 2020, where I worked with Prof. Cho-Jui Hsieh and Prof. Kaiwei Chang on model security. Since joining ByteDance in 2021, I have worked with Prof. Hao Zhou on machine translation and Prof. Quanquan Gu on AI for Science.

Email: zhouyi.naive[-]bytedance[-]com / dugu9sword[-]gmail[-]com / yizhou17[-]fudan[-]edu[-]cn

Selected Research

(A full list can be found on Google Scholar.)

AI for Science

  • SeedFold: Scaling Biomolecular Structure Prediction (Technical Report, 2025)
  • SeedProteo: Accurate De Novo All-Atom Design of Protein Binders (Technical Report, 2025)
  • CryoFM: A Flow-based Foundation Model for Cryo-EM Densities (ICLR 2025)
  • CryoSTAR: Leveraging Structural Prior and Constraints for Cryo-EM Heterogeneous Reconstruction (Nature Methods, 2024)

NLP

  • Deep Equilibrium Non-Autoregressive Sequence Learning (ACL-Findings 2023)
  • The Volctrans GLAT System: Non-autoregressive Translation Meets WMT21 (EMNLP-WMT 2021)
  • Defense against Synonym Substitution-based Adversarial Attacks via Dirichlet Neighborhood Ensemble (ACL 2021)
  • Evaluating and Enhancing the Robustness of Neural Network-based Dependency Parsing Models with Adversarial Examples (ACL 2020)

Talks

Academic Services