Feature Extraction of SDSS Spectra With Improved CNN
Bin Jiang, Haoxin Liu, Qingwei Li, Shuhua Cao, Zhaoyu Chen, Liyun Cheng, and Meixia Qu. "Feature Extraction of SDSS Spectra With Improved CNN." ICCSSE 2019.
CV
Education
- B.S. in GitHub, GitHub University, 2012
- M.S. in Jekyll, GitHub University, 2014
- Ph.D in Version Control Theory, GitHub University, 2018 (expected)
Work experience
- Summer 2015: Research Assistant
- Github University
- Duties included: Tagging issues
- Supervisor: Professor Git
- Fall 2015: Research Assistant
- Github University
- Duties included: Merging pull requests
- Supervisor: Professor Hub
Skills
- Skill 1
- Skill 2
- Sub-skill 2.1
- Sub-skill 2.2
- Sub-skill 2.3
- Skill 3
Publications
Signed Graph Neural Network with Latent Groups
Haoxin Liu, Ziwei Zhang, Peng Cui, Yafeng Zhang, Qiang Cui, Jiashuo Liu, and Wenwu Zhu. "Signed Graph Neural Network with Latent Groups." KDD 2021 Research Track.
Towards Unsupervised Domain Generalization
Xingxuan Zhang, Linjun Zhou, Renzhe Xu, Peng Cui, Zheyan Shen, and Haoxin Liu. "Towards Unsupervised Domain Generalization." CVPR 2022.
LightSGCN: Powering Signed Graph Convolution Network for Link Sign Prediction with Simplified Architecture Design
Haoxin Liu. "LightSGCN: Powering Signed Graph Convolution Network for Link Sign Prediction with Simplified Architecture Design." SIGIR 2022.
Exploiting Global Behavior Contextual Correlation in Sequential Recommendation
Qian Yu, Xiangdong Wu, Chen Yang, Zihao Zhao, Haoxin Liu, and Jingping Shao. "Exploiting Global Behavior Contextual Correlation in Sequential Recommendation." CIKM 2022 DL4SR.
HAPENS: Hardness-Personalized Negative Sampling for Implicit Collaborative Filtering
Haoxin Liu, Pu Zhao, Si Qin, Yong Shi, Mirror Xu, Qingwei Lin, and Dongmei Zhang. "HAPENS: Hardness-Personalized Negative Sampling for Implicit Collaborative Filtering." The Web Conference 2023 Industry Track.
Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning
Haoxin Liu, Harshavardhan Kamarthi, Lingkai Kong, Zhiyuan Zhao, Chao Zhang, and B. Aditya Prakash. "Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning." International Conference on Machine Learning 2024.
LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting
Haoxin Liu, Zhiyuan Zhao, Jindong Wang, Harshavardhan Kamarthi, and B. Aditya Prakash. "LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting." Findings of ACL 2024.
Time-MMD: A New Multi-Domain Multimodal Dataset for Time Series Analysis
Haoxin Liu, Shangqing Xu, Zhiyuan Zhao, Lingkai Kong, Harshavardhan Kamarthi, Aditya B. Sasanur, Megha Sharma, Jiaming Cui, Qingsong Wen, Chao Zhang, and B. Aditya Prakash. "Time-MMD: A New Multi-Domain Multimodal Dataset for Time Series Analysis." Advances in Neural Information Processing Systems 2024.
A Picture is Worth A Thousand Numbers: Enabling LLMs to Reason about Time Series via Visualization
Haoxin Liu, Chenghao Liu, and B. Aditya Prakash. "A Picture is Worth A Thousand Numbers: Enabling LLMs Reason about Time Series via Visualization." NAACL 2025 Main Conference.
Performative Time-Series Forecasting
Zhiyuan Zhao, Haoxin Liu, Alexander RodrÃguez, and B. Aditya Prakash. "Performative Time-Series Forecasting." In Proceedings of the 2025 ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2025).
In-context Pre-trained Time-Series Foundation Models Adapt to Unseen Tasks
Shangqing Xu, Harshavardhan Kamarthi, Haoxin Liu, and B. Aditya Prakash. "In-context Pre-trained Time-Series Foundation Models Adapt to Unseen Tasks." In Proceedings of CIKM 2025.
Talks
Talk 1 on Relevant Topic in Your Field
Talk at UC San Francisco, Department of Testing, San Francisco, California
Tutorial 1 on Relevant Topic in Your Field
Tutorial at UC-Berkeley Institute for Testing Science, Berkeley CA, USA
Talk 2 on Relevant Topic in Your Field
Talk at London School of Testing, London, UK
Conference Proceeding talk 3 on Relevant Topic in Your Field
Conference proceedings talk at Testing Institute of America 2014 Annual Conference, Los Angeles, CA
Teaching
Service and leadership
- Currently signed in to 43 different slack teams