About me
- I am currently a devoted researcher at the Xiaohongshu Inc. Previously, I finished my Ph.D. degree at Zhejiang University, mentored by Prof. Xinggao Liu.
- Research interests: Time-series modeling, Causal Inference, Optimal Transport, Multitask Learning.
🔥 News
- 2025.09: Four papers have been accepted by NeurIPS 2025, associated with time-series forecasting and missing data imputation.
- 2025.08: One first-authored paper has been accepted by TNNLS, associated with missing data imputation.
- 2025.05: We release 🌐DF-o1, a plugin-and-play approach for enhancing time-series direct forecast performance! See more details.
- 2025.04: One first-authored paper has been accepted by KDD 2025, associated with causal inference and debiased recommendation.
- 2025.04: One first-authored paper has been accepted by ICML 2025, associated with implicit feedback recommendation.
- 2025.01: Two first-authored papers have been accepted by ICLR 2025, associated with time-series modeling.
- 2025.01: One first-authored paper has been accepted by ACM TOIS, associated with causal inference and debiased recommendation.
📝 Publications
$\dagger$ for corresponding author.
Time-series modeling and sequence prediction
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NeurIPS 2025Time-o1: time-series forecasting needs transformed label alignment Hao Wang, Licheng Pan, Zhichao Chen, Xu Chen, Qingyang Dai, Lei Wang, Haoxuan Li, Zhouchen Lin -
ICLR 2025Fredf: Learning to forecast in the frequency domain, Hao Wang, Licheng Pan, Zhichao Chen, Degui Yang, Sen Zhang, Yifei Yang, Xinggao Liu, Haoxuan Li, Dacheng Tao. -
ICLR 2025Optimal transport for time series imputation, Hao Wang, Haoxuan Li, Xu Chen, Mingming Gong, Zhichao Chen. -
TAI 2023An accurate and interpretable framework for trustworthy process monitoring, Hao Wang, Zhiyu Wang, Yunlong Niu, Zhaoran Liu, Haozhe Li, Yilin Liao, Yuxin Huang, Xinggao Liu -
ArxivDeepFilter: an instrumental baseline for accurate and efficient process monitoring Hao Wang, Zhichao Chen, Licheng Pan, Xiaoyu Jiang, Yichen Song, Qunshan He, Xinggao Liu. -
CIKM 2023Monotonic neural ordinary differential equation: time-series forecasting for cumulative data Zhichao Chen, Leilei Ding, Zhixuan Chu, Yucheng Qi, Jianmin Huang, Hao Wang$^\dagger$. -
TASE 2024TMoE-P: toward the pareto optimum for multivariate soft sensors Licheng Pan, Hao Wang$^\dagger$, Zhichao Chen, Yuxin Huang, Zhaoran Liu, Qunshan He, Xinggao Liu. -
TASE 2025Controllable mixture-of-experts for multivariate soft sensors Licheng Pan, Hao Wang$^\dagger$, Zhichao Chen, Yuxin Huang, Yunlong Niu, Zhaoran Liu, Qunshan He, Xinggao Liu. -
ArxivMixture of low rank adaptation with partial parameter sharing for time series forecasting Licheng Pan, Zhichao Chen, Haoxuan Li, Guangyi Liu, Zhijian Xu, Zhaoran Liu, Hao Wang$^\dagger$, Ying Wei. -
TII 2022Modeling task relationships in multivariate soft sensor with balanced mixture-of-experts, Yuxin Huang, Hao Wang, Zhaoran Liu, Licheng Pan, Haozhe Li, Xinggao Liu. -
TSMC 2024Improving data-driven inferential sensor modeling by industrial knowledge: A Bayesian perspective Zhichao Chen, Hao Wang, Zhihuan Song, Zhiqiang Ge. -
NeurIPS 2025OLinear: a linear model for time series forecasting in orthogonally transformed domain Wenzhen Yue, Yong Liu, Haoxuan Li, Hao Wang, Xianghua Ying, Ruohao Guo, Bowei Xing, Ji Shi. -
NeurIPS 2025Towards accurate time series forecasting via implicit decoding Xinyu Li, Yuchen Luo, Hao Wang, Haoxuan Li, Liuhua Peng, Feng Liu, Yandong Guo, Kun Zhang, Mingming Gong -
TII 2024Analyzing and improving supervised nonlinear dynamical probabilistic latent variable model for inferential sensors Zhichao Chen, Hao Wang, Guofei Chen, Yiran Ma, Le Yao, Zhiqiang Ge, Zhihuan Song. -
ArxivIntervention-aware forecasting: breaking historical limits from a system perspective, Zhijian Xu, Hao Wang,Yuxuan Bian, Jianyuan Zhong, Xiangyu Wen, Qiang Xu.
User preference modeling and recommendation system
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SIGIR 2022ESCM2: entire space counterfactual multi-task model for post-click conversion rate estimation, Hao Wang, Tai-wei Chang, Tianqiao Liu, Jianmin Huang, Zhichao Chen, Chao Yu, Ruopeng Li, Weizhi Chu. -
TIFS 2024Entire space counterfactual learning for reliable content recommendations, Hao Wang, Zhichao Chen, Zhaoran Liu, Haozhe Li, Degui Yang, Xinggao Liu, Haoxuan Li. -
ICML 2025Unbiased recommender learning from implicit feedback via weakly supervised learning Hao Wang, Zhichao Chen, Haotian Wang, Yanchao Tan, Licheng Pan, Tianqiao Liu, Xu Chen, Haoxuan Li, Zhouchen Lin. -
KDD 2025Proximity matters: Local proximity enhanced balancing for treatment effect estimation Hao Wang, Zhichao Chen, Zhaoran Liu, Xu Chen, Haoxuan Li, Zhouchen Lin. -
TOIS 2025Debiased recommendation via Wasserstein causal balancing Hao Wang, Zhichao Chen, Honglei Zhang, Zhengnan Li, Licheng Pan, Haoxuan Li, Mingming Gong. -
NeurIPS 2023Optimal transport for treatment effect estimation, Hao Wang, Zhichao Chen, Jiajun Fan, Haoxuan Li, Tianqiao Liu, Weiming Liu, Quanyu Dai, Yichao Wang, Zhenhua Dong, Ruiming Tang. <a href=https://scholar.google.com/scholar?oi=bibs&hl=zh-CN&cites=5238722391693176529&as_sdt=5></a>
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NeurIPS 2023Removing hidden confounding in recommendation: a unified multi-task learning approach, Haoxuan Li, Kunhan Wu, Chunyuan Zheng, Yanghao Xiao, Hao Wang, Zhi Geng, Fuli Feng, Xiangnan He, Peng Wu. -
KDD 2024Debiased recommendation with noisy feedback Haoxuan Li, Chunyuan Zheng, Wenjie Wang, Hao Wang, Fuli Feng, Xiao-Hua Zhou. -
ICML 2024Relaxing the accurate imputation assumption in doubly robust learning for debiased collaborative filtering Haoxuan Li, Chunyuan Zheng, Shuyi Wang, Kunhan Wu, Hao Wang, Peng Wu, Zhi Geng, Xu Chen, Xiao-Hua Zhou. -
ArxivConvformer: revisiting transformer for sequential user modeling Hao Wang, Jianxun Lian, Mingqi Wu, Haoxuan Li, Jiajun Fan, Wanyue Xu, Chaozhuo Li, Xing Xie. -
ICLR 2023Learnable behavior control: Breaking atari human world records via sample-efficient behavior selection Jiajun Fan, Yuzheng Zhuang, Yuecheng Liu, Jianye Hao, Bin Wang, Jiangcheng Zhu, Hao Wang, Shu-Tao Xia -
WWW 2024A data-centric multi-objective learning framework for responsible recommendationsSystems Xu Huang, Jianxun Lian, Hao Wang, Hao Liao, Defu Lian, Xing Xie.
Low-quality data modeling and recovery
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ICLR 2025Optimal transport for time series imputation, Hao Wang, Zhengnan Li, Haoxuan Li, Xu Chen, Mingming Gong, Zhichao Chen. -
NeurIPS 2025[A generalized iterative imputation framework for model adaptation and oracle feature utilization], Hao Wang, Zhengnan Li, Zhichao Chen, Xu Chen, Shuting He, Guangyi Liu, Haoxuan Li, Zhouchen Lin -
AAAI 2024Improving neural network generalization on data-limited regression with doubly-robust boosting Hao Wang$^\dagger$. -
TNNLS 2025Robust missing value imputation with proximal optimal transport for low-quality IIoT data Hao Wang, Zhichao Chen, Hui Zheng, Degui Yang, Dangjun Zhao, Buge Liang. -
TII 2024Spot-i: similarity preserved optimal transport for industrial iot data imputation Hao Wang, Zhichao Chen, Zhaoran Liu, Licheng Pan, Hu Xu, Yilin Liao, Haozhe Li, Xinggao Liu. -
TASE 2024Lspt-d: Local similarity preserved transport for direct industrial data imputation Hao Wang, Xinggao Liu, Zhaoran Liu, Haozhe Li, Yilin Liao, Yuxin Huang, Zhichao Chen. -
NeurIPS 2024Rethinking the diffusion models for missing data imputation: A gradient flow perspectiveZhichao Chen, Haoxuan Li, Fangyikang Wang, Odin Zhang, Hu Xu, Xiaoyu Jiang, Zhihuan Song, Hao Wang$^\dagger$. -
CIKM 2024Unsupervised anomaly detection & diagnosis: A stein variational gradient descent approach Zhichao Chen, Leilei Ding, Jianmin Huang, Zhixuan Chu, Qingyang Dai, Hao Wang$^\dagger$. -
TII 2024Denoising diffusion straightforward models for energy conversion monitoring data imputation Hu Xu, Zhaoran Liu, Hao Wang, Changdi Li, Yunlong Niu, Wenhai Wang, Xinggao Liu.
Experiences
- 2025.6 - Present, Researcher, Xiaohongshu Inc.
. - 2022.6 - 2023.6, Research Assistant, Microsoft Research Asia.
. Supervised by Jianxun Lian and Xing Xie - 2021.7 - 2022.6, Research Intern, Alibaba
. Supervised by Wei Chu