About me
Currently doing a postdoc with Prof. Jieming Shi at Hong Kong Polytechnic University. I obtained my doctoral degree in the School of Sofware at Shandong University, advised by Prof. Yilong Yin, worked with Zhongyi Han. In addition, I have done research at Westlake University with Prof. Tailin Wu in 2023.09-2024.02.
Research Direction:
Semi-supervised Learning; Out-of-distribution Detection; AI for Science; Graph learning; Tabular learning
Education :
2024.11-now: Postdoc in Hong Kong Polytechnic University (Hong Kong).
2019.09-2024.06: Ph.D. candidate in Shandong University (Jinan).
2015.09-2019.06: B.E. in Shandong University (Jinan).
Services [Program committee or reviewer for conferences] :
- TNNLS
- IJCAI 2024
- Neural Networks
- ICLR 2024-2025
- TKDE
- CICAI 2023
- ACM MM 2023
- NeurIPS 2023-2024
- ICML 2023-2024-2025
- CVPR 2023
- AAAI 2023-2024
Recent News
- 2025/02/28: 1 paper accepted to Neural Networks.
- 2025/01/23: 1 paper accepted to ICLR 2025.
- 2024/12/03: 1 paper accepted to BIBM 2024.
- 2024/11/17: Congratulations to Yue Yuan (co-advised with Prof. Yilong Yin), for winning the National Scholarship (2023-2024).
- 2024/05/31: 1 paper accepted to IJCV.
- 2024/03/05: 1 paper accepted to ICLR 2024 Workshop ME-FoMo.
- 2024/02/27: 1 paper accepted to CVPR 2024.
- 2023/12/09: 1 paper accepted to AAAI 2024.
- 2023/09/11: 1 paper accepted to Machine Learning Journal.
- 2023/07/26: 2 papers accepted to ACMMM 2023.
- 2023/05/17: 1 paper accepted to TKDE.
- 2023/05/12: 1 paper accepted to PR.
- 2023/02/08: 1 paper accepted to CVPR 2023.
- 2022/11/19: 1 paper accepted to AAAI 2023.
- 2022/11/17: Ph.D. President’s Scholarship (2021-2022)
- 2022/10/19: Ph.D. National Scholarship (2021-2022).
- 2022/09/17: 1 paper accepted to ACML 2022.
- 2022/06/30: 1 paper (oral) accepted to ACMMM 2022.
- 2022/05/20: 1 paper accepted to KBS.
- 2022/03/03: 1 papers accepted to CVPR 2022.
- 2021/12/01: 1 paper (oral) accepted to AAAI 2022.
- 2021/05/31: 1 paper accepted to CICAI 2021.
- 2020/12/02: 1 paper accepted to IPMI 2021.
- 2020/11/23: 1 paper accepted to TCSVT.
Publications
Preprint
Yicong Dong, Rundong He*, Guangyao Chen, Wentao Zhang, Zhongyi Han, Jieming Shi, Yilong Yin.
G-OSR: A Comprehensive Benchmark for Graph Open-Set Recognition. paper
Hao Sun, Rundong He*, Zhongyi Han, Zhicong Lin, Yongshun Gong, Yilong Yin. (Note: * denotes the corresponding author)
CLIP-driven Outliers Synthesis for few-shot OOD detection. paper
Accepted Conference
Rundong He; Yicong Dong; Lanzhe Guo; Yilong Yin; Tailin Wu
Re-Evaluating the Impact of Unseen-Class Unlabeled Data on Semi-Supervised Learning Model. ICLR 2025 (清华推荐A类) paper
Yue Yuan, Rundong He*, Yicong Dong, Zhongyi Han, Yilong Yin. (Note: * denotes the corresponding author)
Discriminability-Driven Channel Selection for Out-of-Distribution Detection. CVPR 2024 (CCF A) code
Rundong He; Yue Yuan; Zhongyi Han; Fan Wang; Wan Su; Yilong Yin; Tongliang Liu; Yongshun Gong.
Exploring Channel-Aware Typical Features for Out-of-Distribution Detection. AAAI 2024 (CCF A) code
Rundong He; Rongxue Li; Zhongyi Han; Yilong Yin.
Topological Structure Learning for Weakly-Supervised Out-of-Distribution Detection. MM 2023 (CCF A)
Yue Yuan; Rundong He; Zhongyi Han; Yilong Yin.
LHAct: Rectifying Extremely Low and High Activations for Out-of-Distribution Detection. MM 2023 (CCF A) code
Rundong He; Zhongyi Han; Xiankai Lu; Yilong Yin.
RONF: Reliable Outlier Synthesis under Noisy Feature Space for Out-of-Distribution Detection. MM 2022 (CCF A, oral)
Rundong He; Zhongyi Han; Xiankai Lu; Yilong Yin.
Safe-Student for Safe Deep Semi-Supervised Learning with Unseen-Class Unlabeled Data. CVPR 2022 (CCF A). code
Rundong He; Zhongyi Han; Yang Yang; Yilong Yin.
Not All Parameters Should be Treated Equally: Deep Safe Semi-Supervised Learning under Class Distribution Mismatch. AAAI 2022 (CCF A, oral). code
Rundong He, Zhongyi Han, Yu Zhang, Xueying He, Xiushan Nie, Yilong Yin.
Robust Anomaly Detection from Partially Observed Anomalies with Augmented Classes. CICAI 2021 paper
Wan Su; Fan Wang; Rundong He; Zhongyi Han; Yilong Yin
Navigating the Unknown: A Novel MGUAN Framework for Medical Image Recognition Across Dynamic Domains. BIBM 2024 (CCF B)
Fan Wang; Zhongyi Han; Zhiyan Zhang; Rundong He; Yilong Yin
MHPL: Minimum Happy Points Learning for Active Source Free Domain Adaptation. CVPR 2023 (CCF A).
Zhongyi Han; Zhiyan Zhang; Fan Wang; Rundong He; Wan Su; Yilong Yin
Discriminability and Transferability Estimation: A Bayesian Source Importance Estimation Approach for Multi-Source-Free Domain Adaptation. AAAI 2023 (CCF A).
Zhongyi Han; Wan Su; Rundong He; Yilong Yin
SNAIL: Semi-Separated Uncertainty Adversarial Learning for Universal Domain Adaptation. ACML 2022
Zhongyi Han, Rundong He, Tianyang Li, Benzheng Wei, Jian Wang, Yilong Yin.
Semi-Supervised Screening of COVID-19 from Positive and Unlabeled Data with Constraint Non-Negative Risk Estimator. (IPMI 2021, 医学顶会). paper
Accepted Journal
Rundong He, Zhongyi Han, Xiushan Nie, Yilong Yin, Xiaojun Chang.
Visual Out-of-Distribution Detection in Open-Set Noisy Environments. International Journal of Computer Vision (IJCV) (CCF A), 2024.
Rundong He; Zhongyi Han; Xiankai Lu; Yilong Yin.
SAFER-STUDENT for Safe Deep Semi-Supervised Learning with Unseen-Class Unlabeled Data. TKDE (CCF A), 2023.
Rundong He; Zhongyi Han; Yilong Yin.
Towards Safe and Robust Weakly-Supervised Anomaly Detection under Subpopulation Shift. KBS (JCR Q1), 2022.
Qikai Wang#, Rundong He#, Yongshun Gong, Chunxiao Ren, Haoliang Sun, Xiaoshui Huang, Yilong Yin. (Note: # denotes the co-first author)
Diverse Teacher-Students for Deep Safe Semi-Supervised Learning under Class Mismatch. Neural Networks (SCI 1区), 2025. paper
Qi Wei, Lei Feng, Haoliang Sun, Ren Wang, Rundong He, Yilong Yin.
Learning Sample-Aware Confidence Threshold for Semi-Supervised Learning. Machine Learning Journal (MLJ) (CCF B), 2023.
Wan Su; Zhongyi Han; Rundong He; Benzheng Wei, Xueying He, and Yilong Yin.
Neighborhood-based Credibility Anchor Learning for Universal Domain Adaptation. PR (JCR Q1), 2023
Yu Zhang, Xiushan Nie, Rundong He, Meng Chen, Yilong Yin.
Normality Learning in Multispace for Video Anomaly Detection. TCSVT (JCR Q1), 2020. paper