StateM
An agent-native runtime for harness scaling, organizing execution around durable states, phase-local context, checked transitions, recoverable runbooks, and versioned procedural practices.
I am a researcher working on agents, efficient deep learning, data-centric AI, and large-scale model training.
My research has led to work such as StateM, InfoBatch, Dataset Growth, Info-Coevolution, and MERIT, with research collaborations across Meta, TikTok, Ali Tongyi Lab, and Tencent Hunyuan Lab.
DD-Ranking · 2026 · One of 15 oral papers
InfoBatch · 2024
CowClip · 2023
TikTok · Efficient data-model co-evolution · 2024-2025
SJTU-UMJI Summer Design Expo · 2019
Industry & research collaborations
Research projects for modern recommendation architectures and AI agents/workflows for engineering production.
Efficient data-model co-evolution for continually improving models and maintaining high-quality growing datasets with affordable cleaning and active annotation.
Research collaboration on data curation for data-centric AI, including research ideation, experiments, and paper writing. This collaboration led to first-author papers at ICLR 2024 Oral and ECCV 2024.
Designed and implemented a Terraform-based system for automatically setting up VM-based distributed training environments on cloud infrastructure.
An agent-native runtime for harness scaling, organizing execution around durable states, phase-local context, checked transitions, recoverable runbooks, and versioned procedural practices.
Lossless training speed-up through unbiased dynamic data pruning, with practical savings across classification, segmentation, detection, vision pretraining, diffusion, and instruction tuning.
An efficient active learning and data-model co-evolution framework for growing datasets and improving models under realistic compute and annotation budgets.
An online algorithm for data cleaning and selection that maintains growing datasets with awareness of cleanliness, diversity, and sampling value.
Zekai Li, Xinhao Zhong, ..., Ziheng Qin, ..., Yang You, Kai Wang.
NeurIPS 2026 ED Track, OralZiheng Qin, Yaxin Lu, Zhangyang Atlas Wang, Kai Wang.
arXiv:2608.15089, 2026Ziheng Qin, Hailun Xu, Wei Chee Yew, Qi Jia, Yang Luo, Kanchan Sarkar, Danhui Guan, Kai Wang, Yang You.
ICML 2025Ziheng Qin, Kai Wang, Zangwei Zheng, Jianyang Gu, Xiangyu Peng, Zhaopan Xu, Daquan Zhou, Lei Shang, Baigui Sun, Xuansong Xie, Yang You.
ICLR 2024 OralZiheng Qin, Zhaopan Xu, Yukun Zhou, Zangwei Zheng, Zebang Cheng, Hao Tang, Lei Shang, Baigui Sun, Xiaojiang Peng, Radu Timofte, Hongxun Yao, Kai Wang, Yang You.
ECCV 2024Zangwei Zheng, Mingyuan Ma, Kai Wang, Ziheng Qin, Xiangyu Yue, Yang You.
ICCV 2023