王英杰（讲师）

»姓名： 王英杰

»系属：自动化系

»学位：博士

»职称：讲师

»专业： 人工智能

»导师类别： 硕导

»电子邮箱：yingjiewang@upc.edu.cn

»联系电话：

»通讯地址：太阳集团tyc234cc

»概况

◎研究方向

基础模型，统计学习理论

◎教育经历

华中农业大学 博士

华中农业大学 本科

◎工作经历

太阳集团tyc234cc 2022 至今

Nanyang Technological University, Research Fellow, 2024-2025

◎学术兼职

IEEE SMC协会感知技术计算委员会委员

IEEE TPAMI、NeurIPS、ICML、ACL、ICLR等审稿人

◎主讲课程

模式识别基础

◎指导研究生及博士后

指导硕博研究生（含高校合作）6人

◎承担项目

国家自然科学基金青年项目       时序深度可加网络的算法与学习理论研究      在研    主持

山东省高等学校青年创新团队项目   多模态大模型泛化能 力与可信性研究       在研   带头人

◎获奖情况

◎荣誉称号

◎著作

《模式识别基础》          刘伟锋，刘宝弟，杨兴浩，张冰锋，王英杰

◎论文

[1] Yingjie Wang, Yutian Zhou, Shi Fu, Yuzhu Chen, Yongcheng Jing, Leszek Rutkowski, Dacheng Tao. Towards a Theoretical Understanding of In-context Learning: Stability and Non-I.I.D Generalisation. ICLR, 2026. CCF A.

[2] Qilu Shen, Wang Yingjie, Xiang Jinhai. Towards Understanding In-Context Learning of Transformers Under Non-I.I.D. Scenarios. AAAI, 2026. CCF A.

[3] Yingjie Wang, Hong Chen, Weifeng Liu, Fengxiang He, Tieliang Gong, Youcheng Fu, Dacheng Tao. Tilted Sparse Additive Models. ICML (Oral), 2023. CCF A.

[4] Yingjie Wang, Xianrui Zhong, Fengxiang He, Hong Chen, Dacheng Tao. Huber Additive Models for Non-stationary Time Series Analysis. ICLR, 2022. CCF A.

[5] Yingjie Wang, Hong Chen, Feng Zheng, Chen Xu, Tieliang Gong, Yanhong Chen. Multi-task Additive Models for Robust Estimation and Automatic Structure Discovery. NeurIPS, 2020. CCF A.

[6] Shi Fu, Yingjie Wang (通讯), Yuzhu Chen, Xinmei Tian, Dacheng Tao. A Theoretical Perspective: How to Prevent Model Collapse in Self-Consuming Training Loops. ICLR, 2025. CCF A.

[7]Shi Fu, Yingjie Wang(通讯), Yuzhu Chen, Li Shen, Dacheng Tao. Self-Verification Provably Prevents Model Collapse in Recursive Synthetic Training. NeurIPS, 2025. CCF A.

[8] Zirui Hu, Zhang Zheng, Wang Yingjie(通讯), Rutkowski Leszek, Dacheng Tao. CoFact: Conformal Factuality Guarantees for Language Models under Distribution Shift. ICLR, 2026. CCF A.

[9] Zirui Hu, Yingjie Wang (通讯), Zheng Zhang, Hong Chen, Dacheng Tao. A Statistical Approach for Controlled Training Data Detection. ICLR, 2025. CCF A.

[10] Shi Fu, Sen Zhang, Yingjie Wang, Xinmei Tian, Dacheng Tao. Towards Theoretical Understandings of Self-Consuming Generative Models. ICML, 2024. CCF A.

[11] Peipei Yuan, Xinge You, Hong Chen, Yingjie Wang, Qinmu Peng, Bin Zou. Sparse Additive Machine With the Correntropy-Induced Loss. IEEE TNNLS, 36(2): 1989-2003, 2025. CCF B.

[12] Liyuan Liu, Yaohui Chen, Weifu Li, Yingjie Wang, Bin Gu, Feng Zheng, Hong Chen. Generalization Bounds of Deep Neural Networks With τ-Mixing Samples. IEEE TNNLS, 36(8): 14596-14610, 2025. CCF B.

[13] Huanjin Yao, Jiaxing Huang, Wenhao Wu, Jingyi Zhang, Yibo Wang, Shunyu Liu, Yingjie Wang, YuXin Song, Haocheng Feng, Li Shen, Dacheng Tao. Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search. NeurIPS (Spotlight), 2025. CCF A.

[14] Kongcheng Zhang, Qi Yao, Shunyu Liu, Yingjie Wang, Baisheng Lai, Jieping Ye, Mingli Song, Dacheng Tao. Consistent Paths Lead to Truth: Self-Rewarding Reinforcement Learning for LLM Reasoning. NeurIPS, 2025. CCF A.

[15] Weifeng Liu, Haoran Yu, YingJie Wang, Baodi Liu, Dapeng Tao, Honglong Chen. IW-ViT: Independence-Driven Weighting Vision Transformer for Out-ofDistribution Generalization. Pattern Recognition, 161: 111308, 2025. CCF B. [16] Jun Chen, Hong Chen, Bin Gu, Guodong Liu, Yingjie Wang, Weifu Li. Error Analysis Affected by Heavy-Tailed Gradients for Non-Convex Pairwise Stochastic Gradient Descent. AAAI, 2025. CCF A.

[17] Wenbin Wang, Yongcheng Jing, Liang Ding, Yingjie Wang, Li Shen, Yong Luo, Bo Du, Dacheng Tao. Retrieval-Augmented Perception: High-resolution Image Perception Meets Visual RAG. ICML, 2025. CCF A.

[18] Yifu Ding, Wentao Jiang, Shunyu Liu, Yongcheng Jing, Jinyang Guo, Yingjie Wang, Jing Zhang, Zengmao Wang, Ziwei Liu, Bo Du, Xianglong Liu, Dacheng Tao. Dynamic Parallel Tree Search for Efficient LLM Reasoning. ACL, 2025. CCF A.

[19] Hong Chen, Yingjie Wang, Feng Zheng, Cheng Deng, Heng Huang. Sparse Modal Additive Model. IEEE TNNLS, 32(6): 2373-2387, 2021. CCF B.

◎专利

《一种基于神经可加模型的油田产量鲁棒预测方法及系统》    王英杰;邓利群;齐玉娟;刘宝弟;刘伟锋