I am Hao Wu, currently a first-year PhD student at Tsinghua University (2025 - 2028 (expected)), my major is Computer Science, advised by Prof. Xiaomeng Huang. Previously, I graduated from the Department of Computer Science at the USTC. During my Master’s studies at USTC, I was also a joint training student in the large model training group of the Machine Learning Platform Department at Tencent. My research interests are as follows:

• Scientific Machine Learning: The ultimate goal of Scientific Machine Learning (SciML) is to accelerate scientific discovery and address complex scientific and engineering challenges by fusing domain knowledge with machine learning. It aims to develop more accurate, efficient, and interpretable predictive models, thereby deepening our understanding of the world and driving innovation.

• World Models: The ultimate goal of Vision-Language Models (VLMs) for Robotics is to enable robots to deeply understand and interact with the world by grounding language in visual perception for intelligent action. It aims to build more versatile, collaborative, and general-purpose robots capable of understanding nuanced human instructions and performing complex tasks in real-world environments.

I have had the privilege of working closely with several esteemed experts, including Dr. Kun Wang, Prof. Qingsong Wen, Prof. Yuxuan Liang, Dr. Xiao Luo, Prof. Yu Zheng, Dr. Chuhan Wu and Dr. Xingjian Shi.

So, Please feel free to contact me for communication and collaboration.

Email: wuhao2022@mail.ustc.edu.cn     Wechat: How_Alexander_Wu

🔥 News

📖 Research Experience

• School of Computer Science and Engineering, Nanyang Technological University
• 2025.07 - Present, Research intern
• Advisor by Kun Wang

• Machine Learning Platform Department, Large model training group, Tencent
• 2023.08 - 2025.07, Research intern
• Mentored by Jinbao Xue

• CityMind Lab, Hong Kong University of Science and Technology (Guangzhou)
• 2023.05 - 2023.08, Research intern
• Advisor Yuxuan Liang

📝 Publications

Scientific Machine Learning

• ICML2025 OneForecast: A Universal Framework for Global and Regional Weather Forecasting. Yuan Gao, Hao Wu, Ruiqi Shu, huanshuo dong, Fan Xu, Rui Ray Chen, Yibo Yan, Qingsong Wen, Xuming Hu, Kun Wang, Jiahao Wu, Li Qing, Hui Xiong, Xiaomeng Huang#. ICML, 2025.

• NeurIPS2024 PURE: Prompt Evolution with Graph ODE for Out-of-distribution Fluid Dynamics Modeling. Hao Wu, Changhu Wang, Fan Xu, Jinbao Xue, Chong Chen, Xian-Sheng Hua, Xiao Luo#. NeurIPS, 2024.

• ICML2024 Prometheus: Out-of-distribution Fluid Dynamics Modeling with Disentangled Graph ODE. Hao Wu, Huiyuan Wang, Kun Wang, Weiyan Wang, ChanganYe, Yangyu Tao, Chong Chen, Xian-Sheng Hua, Xiao Luo#. ICML, 2024.

• Arxiv Spatio-temporal fluid dynamics modeling via physical-awareness and parameter diffusion guidance. Hao Wu, Fan Xu, Yifan Duan, Ziwei Niu, Weiyan Wang, Gaofeng Lu, Kun Wang, Yuxuan Liang#, Yang Wang#. Arxiv, 2024.

Spatio-temporal Prediction

• ICCV2025 Frequency-Aligned Knowledge Distillation for Lightweight Spatiotemporal Forecasting . Yuqi Li, Chuanguang Yang, Hansheng Zeng, Zeyu Dong, Zhulin An, Yongjun Xu, Yingli Tian, Hao Wu#. ICCV, 2025.

• KDD2025 DynST: Dynamic Sparse Training for Resource-Constrained Spatio-Temporal Forecasting. Hao Wu, Haomin Wen, Guibin Zhang, Yutong Xia, Yuxuan Liang, Yu Zheng, Qingsong Wen, Kun Wang#. KDD, 2025.

• AAAI2024 Earthfarseer: versatile spatio-temporal dynamical systems modeling in one model. Hao Wu, Yuxuan Liang, Wei Xiong#, Zhengyang Zhou, Wei Huang, Shilong Wang, Kun Wang#. AAAI, 2024.

• ICLR2024 NuwaDynamics: Discovering and Updating in Causal Spatio-Temporal Modeling. Kun Wang^, Hao Wu^, Yifan Duan, Guibin Zhang, Kai Wang, Xiaojiang Peng, Yu Zheng, Yuxuan Liang#, Yang Wang#. ICLR, 2024.

• TKDE2024 Modeling spatio-temporal dynamical systems with neural discrete learning and levels-of-experts. Kun Wang^, Hao Wu^, Guibin Zhang, Junfeng Fang, Yuxuan Liang, Yuankai Wu, Roger Zimmermann, Yang Wang#. TKDE, 2024.

• ACM MM2024 PastNet: introducing physical inductive biases for spatio-temporal video prediction.Hao Wu, Wei Xiong, Fan Xu, Xiao Luo#, Chong Chen, Xian-Sheng Hua, Haixin Wang#. ACM MM, 2024.

• Arxiv BeamVQ: Aligning Space-Time Forecasting Model via Self-training on Physics-aware Metrics.Hao Wu, Xingjian Shi, Ziyue Huang, Penghao Zhao, Wei Xiong, Jinbao Xue, Yangyu Tao, Xiaomeng Huang, Weiyan Wang #. Arxiv.

Neural Operator Learning

• Arxiv Turb-L1: Achieving Long-term Turbulence Tracing By Tackling Spectral Bias. Hao Wu, Yuan Gao, Ruiqi Shu, Zean Han, Fan Xu, Zhihong Zhu, Qingsong Wen, Xian Wu, Kun Wang, Xiaomeng Huang.

• KDD2024 Neural Manifold Operators for Learning the Evolution of Physical Dynamics. Hao Wu, Kangyu Weng, Shuyi Zhou, Xiaomeng Huang#, Wei Xiong#. KDD, 2024.

• AI4TS(Oral) Neural Manifold Operator for Geophysical Fluid Dynamics Prediction. Wei Xiong, Kun Wang, Yuxuan Liang, Hao Wu#, Xiaomeng Huang#. AI for Time Series (AI4TS) Workshop @ AAAI, 2024.

Information Retrieval

• NeurIPS2023 IDEA: An Invariant Perspective for Efficient Domain Adaptive Image Retrieval. Haixin Wang^, Hao Wu^, Jinan Sun, Shikun Zhang, Chong Chen, Xian-Sheng Hua, Xiao Luo#. NeurIPS, 2023.

Preprints

Turb-L1: Achieving Long-term Turbulence Tracing By Tackling Spectral Bias

Hao Wu, Yuan Gao, Ruiqi Shu, Zean Han, Fan Xu, Zhihong Zhu, Qingsong Wen, Xian Wu, Kun Wang, Xiaomeng Huang

Arxiv, 2025

Paper

Code

Advanced long-term earth system forecasting by learning the small-scale nature

Hao Wu, Yuan Gao, Ruiqi Shu, Kun Wang, Ruijian Gou, Chuhan Wu, Xinliang Liu, Juncai He, Shuhao Cao, Junfeng Fang, Xingjian Shi, Feng Tao, Qi Song, Shengxuan Ji, Yanfei Xiang, Yuze Sun, Jiahao Li, Fan Xu, Huanshuo Dong, Haixin Wang, Fan Zhang, Penghao Zhao, Xian Wu, Qingsong Wen, Deliang Chen, Xiaomeng Huang*

Paper

Code

Selected Publications

Frequency-Aligned Knowledge Distillation for Lightweight Spatiotemporal Forecasting

Yuqi Li, Chuanguang Yang, Hansheng Zeng, Zeyu Dong, Zhulin An, Yongjun Xu, Yingli Tian, Hao Wu#

(ICCV2025, CCF Rank A)

Paper

Code

OneForecast: A Universal Framework for Global and Regional Weather Forecasting

Yuan Gao, Hao Wu, Ruiqi Shu, huanshuo dong, Fan Xu, Rui Ray Chen, Yibo Yan, Qingsong Wen, Xuming Hu, Kun Wang, Jiahao Wu, Li Qing, Hui Xiong, Xiaomeng Huang#

(ICML2025, CCF Rank A)

Paper

Code

DynST: Dynamic Sparse Training for Resource-Constrained Spatio-Temporal Forecasting

Hao Wu, Haomin Wen, Guibin Zhang, Yutong Xia, Yuxuan Liang, Yu Zheng, Qingsong Wen, Kun Wang

(KDD2025, CCF Rank A)

Paper

Code

Neural Manifold Operators for Learning the Evolution of Physical Dynamics

Hao Wu, Kangyu Weng, Shuyi Zhou, Xiaomeng Huang, Wei Xiong

(KDD2025, CCF Rank A)

Paper

Code

Prometheus: Out-of-distribution Fluid Dynamics Modeling with Disentangled Graph ODE

Hao Wu, Huiyuan Wang, Kun Wang, Weiyan Wang, ChanganYe, Yangyu Tao, Chong Chen, Xian-Sheng Hua, Xiao Luo

(ICML2024, CCF Rank A)

Paper

Code

Benchmark

PastNet: Introducing Physical Inductive Biases for Spatio-temporal Video Prediction

Hao Wu, Fan Xu, Chong Chen, Xian-Sheng Hua, Xiao Luo, Haixin Wang

(ACM MM, CCF Rank A)

Paper

Code

Earthfarsser: Versatile Spatio-Temporal Dynamical Systems Modeling in One Model

Hao Wu, Yuxuan Liang, Wei Xiong, Zhengyang Zhou, Wei Huang, Shilong Wang, Kun Wang

(AAAI2024, CCF Rank A)

Paper

Code

PURE: Prompt Evolution with Graph ODE for Out-of-distribution Fluid Dynamics Modeling

Hao Wu, Changhu Wang, Fan Xu, Jinbao Xue, Chong Chen, Xian-Sheng Hua, Xiao Luo

(NeurIPS2024, CCF Rank A)

Paper

Code

NuwaDynamics: Discovering and Updating in Causal Spatio-Temporal Modeling

Kun Wang, Hao Wu, Yifan Duan, Guibin Zhang, Kai Wang, Xiaojiang Peng, Yu Zheng, Yuxuan Liang, Yang Wang

(ICLR2024, THU Rank A spotlight)

Paper

Code

🎖 Honors and Awards

• 2024.09 First-class Academic Scholarship of the University of Science and Technology of China.
• 2022.10 National Scholarship, China (top 0.1% nation-wide).
• 2022.09 First-class Academic Scholarship of the University of Science and Technology of China.

💬 Invited Talks

• 2024.03, Application and Research of GNN in Meteorological Prediction. @ Sun Yat-sen University
• 2023.12, Earthfarseer: versatile spatio-temporal dynamical systems modeling in one model. @ AI TIME
• 2023.06, A Review of Spatio-Temporal Forecasting Models. @ Tsinghua University

💻 Academic service

• PC Member/Conference Reviewer: NeurIPS2023 Conference Reviewers, NeurIPS2024 Conference Reviewers, NeurIPS 2024 Datasets and Benchmarks Track Reviewers, ICLR 2024 Conference Reviewers, ICML 2024 Conference Reviewers, ACMMM 2024 Conference Reviewers, ICLR2025 Conference Reviewers, NeurIPS 2024 Datasets and Benchmarks Track Reviewers, AISTATS 2025 Conference Reviewers, AAAI 2025 Conference Program Committee, NeurIPS2025 Conference Reviewers, ACMMM 2025 Conference Reviewers, ICCV 2025 Conference Reviewers, ICML 2025 Conference Reviewers.

👨🏻 Miscellaneous

• 🏀 I am a big fan of basketball, i love Kobe Bryant and i like Fadeaway Shot. I also like Curry.
• 👑 I am very interested in history.