Yunnan UniversityI received my PhD in Software Engineering from Chongqing University in 2025, where I am fortunate to be advised by Prof. Li Liu. Before that, I earned my Master’s degree in Software Engineering at Yunnan University in 2021, guided by Prof. Shin-Jye Lee, and Associate Prof. Xin Jin. Moreover, I am supported by the Young Elite Scientists Sponsorship Program by the CAST-Doctoral Student Special Plan (via CCF).
My research interests lie in generative models, computer vision, and causal learning, with a particular focus on causality in image editing. If you are interested in discussing potential collaborations or shared research interests, please do not hesitate to contact me at [email](huangshanshan9633@163.com).
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Chongqing UniversityPh.D. in Software EngineeringSep. 2021 - Jul. 2025 -
Yunnan UniversityM.S. in Software EngineeringSep. 2018 - Jul. 2021
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Nantong UniversityB.S. in Software EngineeringSep. 2014 - Jul. 2018
Honors & Awards
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Outstanding Graduate of Chongqing2025
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National Scholarship (Ph.D.), Ministry of Education of China2023
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Outstanding Graduate of Yunnan Province2021
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Outstanding All-Round Student of Yunnan Province2021
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National Scholarship (M.Sc.), Ministry of Education of China2020
News
Selected Publications (view all )
CDSF: A Curvature-Driven Semi-Supervised Framework with Dynamic Receptive Fields for Fine-Grained Vehicle Component Segmentation
Zhili Gong, Chunyuan Zheng, Shanshan Huang, Huayi Yang, Guoxin Su, Li Liu
Knowledge-Based Systems 2025
We propose CDSF, a curvature-driven semi-supervised framework with dynamic receptive fields designed for fine-grained vehicle component segmentation. Published in Knowledge-Based Systems (KBS).
CDSF: A Curvature-Driven Semi-Supervised Framework with Dynamic Receptive Fields for Fine-Grained Vehicle Component Segmentation
Zhili Gong, Chunyuan Zheng, Shanshan Huang, Huayi Yang, Guoxin Su, Li Liu
Knowledge-Based Systems 2025
We propose CDSF, a curvature-driven semi-supervised framework with dynamic receptive fields designed for fine-grained vehicle component segmentation. Published in Knowledge-Based Systems (KBS).
Mitigating Data Imbalance in Time Series Classification Based on Counterfactual Minority Samples Augmentation
Lei Wang, Shanshan Huang, Chunyuan Zheng, Jun Liao, Haoxuan Li, Li Liu
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2025
This paper addresses data imbalance in time series classification via counterfactual minority sample augmentation.
Mitigating Data Imbalance in Time Series Classification Based on Counterfactual Minority Samples Augmentation
Lei Wang, Shanshan Huang, Chunyuan Zheng, Jun Liao, Haoxuan Li, Li Liu
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2025
This paper addresses data imbalance in time series classification via counterfactual minority sample augmentation.
Visual Representation Learning through Causal Intervention for Controllable Image Editing
Shanshan Huang, Haoxuan Li, Chunyuan Zheng, Lei Wang, Guorui Liao, Huayi Yang, Li Liu
CVPR 2025
This paper proposes a causal intervention-based representation learning method for controllable image editing. Accepted as a CVPR 2025 Highlight paper (top 2.9%).
Visual Representation Learning through Causal Intervention for Controllable Image Editing
Shanshan Huang, Haoxuan Li, Chunyuan Zheng, Lei Wang, Guorui Liao, Huayi Yang, Li Liu
CVPR 2025
This paper proposes a causal intervention-based representation learning method for controllable image editing. Accepted as a CVPR 2025 Highlight paper (top 2.9%).
Text-Driven Fashion Image Editing with Compositional Concept Learning and Counterfactual Abduction
Shanshan Huang, Haoxuan Li, Chunyuan Zheng, Mingyuan Ge, Wei Gao, Lei Wang, Li Liu
CVPR 2025
We propose a novel text-driven framework that integrates compositional concept learning and counterfactual abduction for fashion image editing. Accepted at CVPR 2025.
Text-Driven Fashion Image Editing with Compositional Concept Learning and Counterfactual Abduction
Shanshan Huang, Haoxuan Li, Chunyuan Zheng, Mingyuan Ge, Wei Gao, Lei Wang, Li Liu
CVPR 2025
We propose a novel text-driven framework that integrates compositional concept learning and counterfactual abduction for fashion image editing. Accepted at CVPR 2025.
CAP: Causal Air Quality Index Prediction Under Interference with Unmeasured Confounding
Huayi Yang, Chunyuan Zheng, Guorui Liao, Shanshan Huang, Jun Liao, Zhili Gong, Haoxuan Li, Li Liu
The Web Conference (WWW) 2025
A causal model for air quality index prediction under interference and unmeasured confounding.
CAP: Causal Air Quality Index Prediction Under Interference with Unmeasured Confounding
Huayi Yang, Chunyuan Zheng, Guorui Liao, Shanshan Huang, Jun Liao, Zhili Gong, Haoxuan Li, Li Liu
The Web Conference (WWW) 2025
A causal model for air quality index prediction under interference and unmeasured confounding.
HiPoser: 3D Human Pose Estimation with Hierarchical Shared Learning at Parts-Level Using Inertial Measurement Units
Guorui Liao, Chunyuan Zheng, Li Cheng, Haoyu Xie, Shanshan Huang, Jun Liao, Haoxuan Li, Li Liu
AAAI Conference on Artificial Intelligence (AAAI) 2025
A novel hierarchical shared learning approach for 3D human pose estimation using IMUs.
HiPoser: 3D Human Pose Estimation with Hierarchical Shared Learning at Parts-Level Using Inertial Measurement Units
Guorui Liao, Chunyuan Zheng, Li Cheng, Haoyu Xie, Shanshan Huang, Jun Liao, Haoxuan Li, Li Liu
AAAI Conference on Artificial Intelligence (AAAI) 2025
A novel hierarchical shared learning approach for 3D human pose estimation using IMUs.
Controllable Image Synthesis Methods, Applications and Challenges: A Comprehensive Survey
Shanshan Huang, Qingsong Li, Jun Liao, Shu Wang, Li Liu, Lian Li
Artificial Intelligence Review 2024
A comprehensive survey on controllable image synthesis methods, applications and challenges.
Controllable Image Synthesis Methods, Applications and Challenges: A Comprehensive Survey
Shanshan Huang, Qingsong Li, Jun Liao, Shu Wang, Li Liu, Lian Li
Artificial Intelligence Review 2024
A comprehensive survey on controllable image synthesis methods, applications and challenges.
Multi-attentional Causal Intervention Networks for Medical Image Diagnosis
Shanshan Huang, Lei Wang, Jun Liao, Li Liu
Knowledge-Based Systems 2024
Multi-attentional causal intervention networks for accurate medical image diagnosis.
Multi-attentional Causal Intervention Networks for Medical Image Diagnosis
Shanshan Huang, Lei Wang, Jun Liao, Li Liu
Knowledge-Based Systems 2024
Multi-attentional causal intervention networks for accurate medical image diagnosis.
Pareto Invariant Representation Learning for Multimedia Recommendation
Shanshan Huang*, Haoxuan Li*, Qingsong Li, Chunyuan Zheng, Li Liu (* equal contribution)
ACM Multimedia 2023
This work proposes Pareto invariant representation learning for multimedia recommendation tasks.
Pareto Invariant Representation Learning for Multimedia Recommendation
Shanshan Huang*, Haoxuan Li*, Qingsong Li, Chunyuan Zheng, Li Liu (* equal contribution)
ACM Multimedia 2023
This work proposes Pareto invariant representation learning for multimedia recommendation tasks.
Score-based Causal Feature Selection for Cancer Risk Prediction
Shanshan Huang, Qingsong Li, Lei Wang, Yuanhao Wang, Li Liu
IEEE ICME 2023
A score-based causal feature selection method for cancer risk prediction.
Score-based Causal Feature Selection for Cancer Risk Prediction
Shanshan Huang, Qingsong Li, Lei Wang, Yuanhao Wang, Li Liu
IEEE ICME 2023
A score-based causal feature selection method for cancer risk prediction.
Deep Learning for Image Colorization: Current and Future Prospects
Shanshan Huang, Xin Jin, Qian Jiang, Li Liu
Engineering Applications of Artificial Intelligence (EAAI) 2022
A survey of current and future deep learning methods for image colorization.
Deep Learning for Image Colorization: Current and Future Prospects
Shanshan Huang, Xin Jin, Qian Jiang, Li Liu
Engineering Applications of Artificial Intelligence (EAAI) 2022
A survey of current and future deep learning methods for image colorization.
Semisupervised Remote Sensing Image Fusion using Multiscale Conditional GAN with Siamese Structure
Xin Jin, Shanshan Huang†, Qian Jiang, Shin-Jye Lee, Liwen Wu, Shaowen Yao
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2021
A semisupervised image fusion method for remote sensing using multiscale conditional GANs.
Semisupervised Remote Sensing Image Fusion using Multiscale Conditional GAN with Siamese Structure
Xin Jin, Shanshan Huang†, Qian Jiang, Shin-Jye Lee, Liwen Wu, Shaowen Yao
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2021
A semisupervised image fusion method for remote sensing using multiscale conditional GANs.