About Me

I am an Associate Professor at the School of Software, Shandong University. I received my PhD (2020) and Bachelor (2014) degrees in Engineering from Shandong University, under the supervision of Prof. Yilong Yin. In 2016 I visited Prof. Shuo Li's group at Western University, Canada as a visiting student. Supported by the China Scholarship Council (CSC), I spent one and a half years at the University of Wisconsin–Madison under the supervision of Prof. Vikas Singh. I also pursued an internship at the Inception Institute of Artificial Intelligence (IIAI), UAE.

My research interests span both machine learning and computer vision, including meta-learning, weakly supervised learning, and generative models.

News

• 2026.07Zichen and I attended ICML 2026, Seoul, South Korea. What a massive turnout!
• 2026.06One paper was accepted by ECCV 2026. Congrats to Yaqi Zhao.
• 2026.05Two papers were accepted by ICML 2026. Congrats to Zichen Zhong and Lehui Li.
• 2025.11Dr. Nick Tobin from Karolinska Institute visited our group for academic exchange.
• 2025.11Gave a talk on “Human–AI Collaborative Methods and Applications in Medical Decision-Making” at the 8th SDU–KI Joint Symposium.
• 2026.08Ren Wang attended IJCAI 2025, Satellite Event in Guangzhou.
• 2025.06Attended CVPR 2025, Nashville, Tennessee, United States. An unforgettable trip, marred by frustrations.
• 2025.04Two papers were accepted by IJCAI 2025. Congrats to Ren Wang and Shilu Yuan.
• 2025.02One paper was accepted by CVPR 2025. Congrats to Ren Wang.
• 2024.09Gave a talk on “SSL-based noisy label learning and beyond” at Guilin University of Electronic Technology.
• 2024.07One paper was accepted by IJCV. Congrats to all co-authors.
• 2023.12Awarded the title of Young Expert of Taishan Scholars in Shandong Province.

Selected Publications

Please refer to Google Scholar for the complete list. (# denotes equal contribution, * denotes corresponding author.)

Generative Models

ICML 2026

Riemannian MeanFlow for One-Step Generation on Manifolds

Zichen Zhong, Haoliang Sun*, Yukun Zhao, Yongshun Gong, Yilong Yin

International Conference on Machine Learning (ICML), 2026.

arXiv Code

ICCV 2019

DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer

Haoliang Sun*, Ronak Mehta, Hao H. Zhou, Zhichun Huang, Sterling C. Johnson, Vivek Prabhakaran, Vikas Singh

IEEE International Conference on Computer Vision (ICCV), 2019.

arXiv Code

Robust Learning with Noisy Labels

ECCV 2026

Holistic Optimal Label Selection for Robust Prompt Learning under Partial Labels

Yaqi Zhao, Haoliang Sun*, Yating Wang, Yongshun Gong, and Yilong Yin

European Conference on Computer Vision (ECCV), 2026.

arXiv Code

IJCV 2025

Variational Rectification Inference for Learning with Noisy Labels

Haoliang Sun#*, Qi Wei#, Lei Feng, Yupeng Hu, Fan Liu, Hehe Fan, Yilong Yin

International Journal of Computer Vision (IJCV), 2025.

PDF Code

SCI 2024

面向标签噪声学习的联合训练框架 (Joint Training Framework for Label Noise Learning)

Qi Wei, Haoliang Sun*, Yuling Ma, Yilong Yin

Scientia Sinica Informationis (中国科学:信息科学), 2024.

PDF

CVPR 2023

Fine-Grained Classification with Noisy Labels

Qi Wei, Lei Feng, Haoliang Sun*, Ren Wang, Chenhui Guo, Yilong Yin

IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.

arXiv

ECCV 2022

Self-Filtering: A Noise-Aware Sample Selection for Label Noise with Confidence Penalization

Qi Wei, Haoliang Sun*, Xiankai Lu, Yilong Yin

European Conference on Computer Vision (ECCV), 2022.

arXiv

PR 2021

Learning to Rectify for Robust Learning with Noisy Labels

Haoliang Sun#*, Chenhui Guo#, Qi Wei, Zhongyi Han, Yilong Yin

Pattern Recognition (PR), 2021.

arXiv Code

Learning in a Dynamic Environment

IJCAI 2025

Improving Generalization in Meta-Learning via Meta-Gradient Augmentation

Ren Wang, Haoliang Sun*, Yuxiu Lin, Xinxin Zhang, Yilong Yin

International Joint Conference on Artificial Intelligence (IJCAI), 2025.

URL

CVPR 2025

SeqMvRL: A Sequential Fusion Framework for Multi-view Representation Learning

Ren Wang, Haoliang Sun*, Yuxiu Lin, Chuanhui Zuo, Yongshun Gong, Yilong Yin, Wenjia Meng

IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2025.

PDF

ML 2024

Learning Sample-Aware Threshold for Semi-Supervised Learning

Qi Wei, Lei Feng, Haoliang Sun*, Ren Wang, Rundong He, Yilong Yin

Machine Learning, 2024 (ACML 2023 Journal Track).

PDF

PR 2023

Attentional Prototype Inference for Few-Shot Segmentation

Haoliang Sun*, Xiankai Lu, Haochen Wang, Yilong Yin, Xiantong Zhen, Cees G. M. Snoek, Ling Shao

Pattern Recognition (PR), 2023.

arXiv Code

CVPR 2023

MetaViewer: Towards A Unified Multi-View Representation

Ren Wang, Haoliang Sun*, Yuling Ma, Xiaoming Xi, Yilong Yin

IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.

arXiv

Kernel Methods

ICML 2020

Learning to Learn Kernels with Variational Random Features

Xiantong Zhen#, Haoliang Sun#, Yingjun Du#, Jun Xu, Yilong Yin, Ling Shao, Cees Snoek

International Conference on Machine Learning (ICML), 2020.

arXiv Code

CVPR 2017

Learning Deep Match Kernels for Image-Set Classification

Haoliang Sun*, Xiantong Zhen, Yuanjie Zheng, Gongping Yang, Yilong Yin, Shuo Li

IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.

PDF

IPMI 2017

Directly Estimating Spinal Cobb Angles by Structured Multi-Output Regression

Haoliang Sun*, Xiantong Zhen, Chris Bailey, Parham Rasoulinejad, Yilong Yin, Shuo Li

Information Processing in Medical Imaging (IPMI), Oral Paper, 2017.

arXiv

People

Current Students

Alumni

Education & Experience

• 2020PhD in Engineering, Shandong University (advisor: Prof. Yilong Yin)
• 2014Bachelor in Engineering, Shandong University
• 2019Research Intern, Inception Institute of Artificial Intelligence (IIAI), UAE
• 2018–2019Jointly trained PhD student, University of Wisconsin–Madison (advisor: Prof. Vikas Singh; supported by CSC)
• 2016Jointly trained PhD student, Western University, Canada (advisor: Prof. Shuo Li)

Honors & Awards

• 2024 — Shandong Provincial Science and Technology Progress Award.
• 2023 — Young Expert of Taishan Scholars, Shandong Province.

Professional Services

Courses

• 人工智能基础 Foundations of AI
  2025–2026
• 高级机器学习 Advanced Machine Learning
  2024–2025
• 数理逻辑 Mathematical Logic
  2023–2024
• 编译原理与技术 Compilation Principles and Techniques
  2024–2026

Contact