Yi Zhou (周奕)

I'm currently employed as a research scientist at ByteDance Research, intensively focusing on AI for science and Artificial Genreral Intelligence. Natural language processing (NLP) is my "native language".

I established the cryo-EM research team at Bytedance Research, and our first work CryoSTAR was accepted by Nature Methods. I believe that our effort to empowering AI for biology is well recognized by biologists.

Besides that, I have a fair understanding and experience in deep generative modeling (protein design, 3d generation, etc.), traditional NLP tasks (labeling, parsing, translation, etc.), and of course, the popular LLM.

I was part of the Fudan NLP group and earned my Master's degree from Fudan University (2017~2021), under the mentorship of Prof. Xiaoqing Zheng. In 2020, I gained invaluable experience visiting the University of California, Los Angeles. During this visit, I had the opportunity to collaborate with Prof. Cho-Jui Hsieh and Prof. Kaiwei Chang, focusing primarily on the topic of model security in the field of NLP. Since 2021, I joined the ByteDance AI Lab, where I have been working closely with Prof. Hao Zhou(2021~2022) and Prof. Quanquan Gu(2023~).

Email: zhouyi.naive[-]bytedance[-]com / dugu9sword[-]gmail[-]com

cryostar
A neural network based framework for recovering conformational heterogenity of protein complexes.
https://github.com/bytedance/cryostar

torch-random-fields
A library for building markov random fields (MRF) with complex topology with pytorch, it is optimized for batch training on GPU.
https://github.com/dugu9sword/torch_random_fields

manytasks
A lightweight tool for deploying many tasks automatically, without any modification to your code.
https://github.com/dugu9sword/manytasks

paragen
A PyTorch deep learning framework for parallel sequence generation and beyond.
https://github.com/bytedance/paragen

Reviewing for AI conferences:

Reviewing for AI Journals:

PARAGEN : A Parallel Generation Toolkit Jiangtao Feng, Yi Zhou, Jun Zhang, Xian Qian, Liwei Wu, Zhexi Zhang, Yanming Liu, Mingxuan Wang, Lei Li, Hao Zhou https://arxiv.org/abs/2210.03405

CryoFM: A Flow-based Foundation Model for Cryo-EM Densities Yi Zhou, Yilai Li, Jing Yuan, Quanquan Gu https://arxiv.org/abs/2410.08631 Equal contribution.

CryoSTAR: Leveraging Structural Prior and Constraints for Cryo-EM Heterogeneous Reconstruction Yilai Li, Yi Zhou, Jing Yuan, Fei Ye, Quanquan Gu Nature Methods Equal contribution.

CryoSTAR: Cryo-EM Heterogeneous Reconstruction of Atomic Models with Structural Regularization Yi Zhou, Yilai Li, Jing Yuan, Fei Ye, Quanquan Gu NeurIPS 2023 AI4D3 Workshop Equal contribution.

Structure-informed Language Models Are Protein Designers Zaixiang Zheng, Yifan Deng, Dongyu Xue, Yi Zhou, Fei Ye, Quanquan Gu ICML 2023 Oral presentation.

Deep Equilibrium Non-Autoregressive Sequence Learning Zaixiang Zheng, Yi Zhou, Hao Zhou ACL-Findings 2023

Regularized Molecular Conformation Fields Lihao Wang, Yi Zhou, Yiqun Wang, Xiaoqing Zheng, Xuanjing Huang, Hao Zhou NeurIPS 2022 Spotlight.

Zero-Shot 3D Drug Design by Sketching and Generating Siyu Long, Yi Zhou, Xinyu Dai, Hao Zhou NeurIPS 2022 Spotlight.

Defense against Synonym Substitution-based Adversarial Attacks via Dirichlet Neighborhood Ensemble Yi Zhou, Xiaoqing Zheng, Cho-Jui Hsieh, Kai-wei Chang, Xuanjing Huang ACL 2021

Chinese Named Entity Recognition Augmented with Lexicon Memory Yi Zhou, Xiaoqing Zheng, Xuanjing Huang JCST 2021

The Volctrans GLAT System: Non-autoregressive Translation Meets WMT21 Lihua Qian, Yi Zhou, Zaixiang Zheng, Yaoming Zhu, Zehui Lin, Jiangtao Feng, Shanbo Cheng, Lei Li, Mingxuan Wang, Hao Zhou WMT 2021 Equal contribution.

On the Transferability of Adversarial Attacks against Neural NLP Models Liping Yuan, Xiaoqing Zheng, Yi Zhou, Cho-Jui Hsieh, Kai-wei Chang EMNLP 2021

Generating Responses with a Given Syntactic Pattern in Chinese Dialogues Yi Zhou, Xiaoqing Zheng, Xuanjing Huang TASLP 2021

Cross-Lingual Dependency Parsing by POS-Guided Word Reordering Lu Liu, Yi Zhou, Jianhan Xu, Xiaoqing Zheng, Kai-wei Chang, Xuanjing Huang EMNLP 2020

Evaluating and Enhancing the Robustness of Neural Network-based Dependency Parsing Models with Adversarial Examples Xiaoqing Zheng, Jiehang Zeng, Yi Zhou, Cho-Jui Hsieh, Minhao Cheng, Xuanjing Huang ACL 2020 Equal contribution.

RNN-Based Sequence Preserved Attention for Dependency Parsing Yi Zhou, Junying Zhou, Lu Liu, Jiangtao Feng, Haoyuan Peng, Xiaoqing Zheng AAAI 2018 Oral presentation.

Attention Based Belief or Disbelief Feature Extraction for Dependency Parsing Haoyuan Peng, Lu Liu, Yi Zhou, Junying Zhou, Xiaoqing Zheng AAAI 2018