🙋‍♂️ About me 🙋‍♂️

I am a PhD student at the College of Informatics, Huazhong Agricultural University (2022.9-), advised by Professor Hong Chen. I obtained my M.S. degree at the College of Science, Huazhong Agricultural University (2020.9-2022.6) and my B.S. degree at the School of Mathmatics, Taiyuan University of Technology (2016.9-2020.6). I previously visited the Gaoling School of Artificial Intelligence, Renmin University of China, advised by Professor Yong Liu (Oct. 2023 - Mar. 2024). Subsequently, I was jointly advised by Professor Yiming Ying, University of Sydney, for a joint PhD program of Chinese Government Scholarship to Study Abroad (Jul. 2024 - Dec. 2025). Currently, I am working as Postdoctoral Fellow at City University of Hong Kong, advised by Professor Ziye Ma.

💻 Research Interests 💻

My research interests lie in the theory and application of machine learning, particularly in statistical machine learning theory, unsupervised learning, and agent learning. If you want to have a chat, please always feel free to contact me through Email!

🎊 News 🎊

The paper “How does Labeling Error Impact Contrastive Learning? A Perspective from Data Dimensionality Reduction” was accepted as a poster of ICML 2025.

📄 Preprints 📄

Clustering-Guided Multi-Layer Contrastive Representation Learning for Citrus Disease Classification Paper
Jun Chen, Yonghua Yu, Weifu Li, Yaohui Chen, Hong Chen*. 2025.

📄 Publications 📄

Conferences:

How does Labeling Error Impact Contrastive Learning? A Perspective from Data Dimensionality Reduction Paper
Jun Chen, Hong Chen*, Yonghua Yu, Yiming Ying. ICML, 2025.
Error Analysis Affected by Heavy-Tailed Gradients for Non-Convex Pairwise Stochastic Gradient Descent Paper
Jun Chen, Hong Chen*, Bin Gu, Guodong Liu, Yingjie Wang, Weifu Li*. AAAI, 2025.
How Does Black-Box Impact the Learning Guarantee of Stochastic Compositional Optimization? Paper
Jun Chen, Hong Chen*, Bin Gu. NeurIPS, 2024.
Fine-Grained Theoretical Analysis of Federated Zeroth-Order Optimization Paper
Jun Chen, Hong Chen*, Bin Gu, Hao Deng*. NeurIPS, 2023.
Stability-Based Generalization Analysis for Mixtures of Pointwise and Pairwise Learning Paper
Jiahuan Wang, Jun Chen, Hong Chen*, Bin Gu, Weifu Li, Xin Tang. AAAI, 2023.
On the Stability and Generalization of Triplet Learning Paper
Jun Chen, Hong Chen*, Xue Jiang, Bin Gu, Weifu Li, Tieliang Gong, Feng Zheng. AAAI, 2023.

Journals:

Predicting and Visualizing Citrus Color Transformation Using A Deep Mask-Guided Generative Network Paper
Zehan Bao#, Weifu Li#, Jun Chen, Hong Chen, Vijay John, Chi Xiao*, Yaohui Chen*. Plant Phenomics, 2023.
Improving Human Intuition for Vision-Based Freshness Prediction of Citrus Reticulata Blanco Using Machine Learning Paper
Yonghua Yu#, Hao Deng#, Jun Chen, Yunjiang Cheng, Rangwei Xu, Shanjun Li*, Yaohui Chen*. Scientia Horticulturae, 2023.
Two-stage Hierarchical Framework for Solar Flare Prediction Paper
Hao Deng, Yuting Zhong, Hong Chen*, Jun Chen, Jingjing Wang, Yanhong Chen, Bingxian Luo. The Astrophysical Journal Supplement Series, 2023.
Two-Stage Solar Flare Forecasting Based on Convolutional Neural Networks Paper
Jun Chen, Weifu Li, Shuxin Li, Hong Chen*, Xuebin Zhao, Jiangtao Peng, Yanhong Chen, Hao Deng. Space: Science & Technology, 2022.
RU-net: A Residual U-net for Automatic Interplanetary Coronal Mass Ejection Detection Paper
Jun Chen, Hao Deng*, Shuxin Li, Weifu Li, Hong Chen, Yanhong Chen, Bingxian Luo. *The Astrophysical Journal Supplement Series, 2022.
基于深度学习的太阳黑子Wilson山磁类型识别方法论文
李书馨, 赵学斌, 陈君, 李伟夫, 陈洪, 陈艳红, 崔延美, 袁天娇. 空间科学学报, 2022.

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