[1] Learning with Small Data. (KDD 2020 [Website] [Slides] [YouTube] [Bilibili]) (WSDM 2020 [Website]) (AAAI 2021)

[2] Meta-learning and Automated Machine Learning: Approaches and Applications​. (IJCAI 2020 [Website])

[1] Huaxiu Yao, Linjun Zhang, Chelsea Finn, Meta-Learning with Fewer Tasks through Task Interpolation, arXiv 2106.02695. [arXiv]

[2] Ying Wei, Peilin Zhao, Huaxiu Yao, Junzhou Huang, Transferable Neural Processes for Hyperparameter Optimization, arXiv 1909.03209 (the short version is published in NeurIPS 2019 Workshop on Meta-Learning). [arXiv]

[3] Ali Ghadirzadeh, Petra Poklukar, Xi Chen, Huaxiu Yao, Hossein Azizpour, Mårten Björkman, Chelsea Finn, Danica Kragic, Few-Shot Learning With Weak Supervision, ICLR 2021 Workshop on Learning to Learn. [Openreview] [Poster]

[1] Huaxiu Yao*, Longkai Huang*, Linjun Zhang, Ying Wei, Li Tian, James Zou, Junzhou Huang, Zhenhui Li, Improving Generalization in Meta-learning via Task Augmentation, in Proceeding of the Thirty-eighth International Conference on Machine Learning (ICML 2021), virtual, Jul. 2021. [PDF] [Supplementary] [Code] [Slides] [Poster] [arXiv]

[2] Jiatu Shi*, Huaxiu Yao* (equal contribution, alphabetical order), Xian Wu, Tong Li, Zedong Lin, Tengfei Wang, Binqiang Zhao, Relation-aware Meta-learning for E-commerce Market Segment Demand Prediction with Limited Records, in Proceeding of the 14th ACM International Conference on Web Search and Data Mining (WSDM 2021), virtual, Mar. 2021. [PDF] [arXiv]

[3] Porter Jenkins, Ahmad Farag, Stockton Jenkins, Huaxiu Yao, Suhang Wang, Zhenhui Li, Neural Utility Functions, in Proceeding of the Thirty-fifth AAAI Conference on Artificial Intelligence (AAAI 2021), virtual, Feb. 2021. [PDF]

[4] Chuxu Zhang, Huaxiu Yao, Lu Yu, Chao Huang, Dongjing Song, Haifeng Chen, Meng Jiang, Nitesh V. Chawla, Inductive Contextual Relation Learning for Personalization, ACM Transactions on Information System (TOIS) 39, no. 3 (2021): 1-22. [PDF]

[5] Huaxiu Yao, Yingbo Zhou, Mehrdad Mahdavi, Zhenhui Li, Richard Socher, Caiming Xiong, Online Structured Meta-learning, in Proceeding of the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS 2020), virtual, Dec. 2020. [PDF] [Supplementary] [Code] [Slides] [Poster] [arXiv]

[6] Huaxiu Yao, Xian Wu, Zhiqiang Tao, Yaliang Li, Bolin Ding, Ruirui Li, Zhenhui Li, Automated Relational Meta-learning, in Proceeding of the Eighth International Conference on Learning Representations (ICLR 2020), virtual, Apr. 2020. [Openreview] [PDF] [Code] [Slides] [arXiv]

[7] Huaxiu Yao, Chuxu Zhang, Ying Wei, Meng Jiang, Suhang Wang, Junzhou Huang, Nitesh V. Chawla, Zhenhui Li, Graph Few-shot Learning via Knowledge Transfer, in Proceeding of the Thirty-fourth AAAI Conference on Artificial Intelligence (AAAI 2020), New York, NY, Feb. 2020 (the short version is published in NeurIPS 2019 Graph Representation Learning Workshop). [PDF] [Full Paper] [Code] [arXiv]

[8] Chuxu Zhang, Huaxiu Yao, Chao Huang, Meng Jiang, Zhenhui Li, Nitesh V. Chawla, Few-Shot Knowledge Graph Completion, in Proceeding of the Thirty-fourth AAAI Conference on Artificial Intelligence (AAAI 2020), New York, NY, Feb. 2020. [PDF] [Code] [Poster] [arXiv]

[9] Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Charu Aggarwal, Prasenjit Mitra, Suhang Wang, Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values, in Proceeding of the Thirty-fourth AAAI Conference on Artificial Intelligence (AAAI 2020), New York, NY, Feb. 2020. [PDF] [arXiv]

[10] Xinshi Zang, Huaxiu Yao, Guanjie Zheng, Nan Xu, Kai Xu, Zhenhui Li, MetaLight: Value-based Meta-reinforcement Learning for Online Universal Traffic Signal Control, in Proceeding of the Thirty-fourth AAAI Conference on Artificial Intelligence (AAAI 2020), New York, NY, Feb. 2020. [PDF] [Code] [Poster]

[11] Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Yiqi Wang, Jiliang Tang, Charu Aggarwal, Prasenjit Mitra, Suhang Wang, Investigating and Mitigating Degree-Related Biases in Graph Convolutional Networks, in Proceeding of the 29th ACM International Conference on Information and Knowledge Management (CIKM 2020), Galway, Ireland, Oct. 2020. [PDF] [arXiv]

[12] Xianfeng Tang, Yandong Li, Yiwei Sun, Huaxiu Yao, Prasenjit Mitra, Suhang Wang, Transferring Robustness for Graph Neural Network Against Poisoning Attacks, in Proceeding of the 13th ACM International Conference on Web Search and Data Mining (WSDM 2020), Houston, TX, Feb. 2020. [PDF] [Code] [arXiv]

[13] Huaxiu Yao, Ying Wei, Junzhou Huang, Zhenhui Li, Hierarchically Structured Meta-learning, in Proceeding of the 36th International Conference on Machine Learning (ICML 2019), Long Beach, CA, June 2019. [PDF] [Supplementary] [Slides] [Poster] [Code] [arXiv]

[14] Huaxiu Yao, Yiding Liu, Ying Wei, Xianfeng Tang, Zhenhui Li, Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal Prediction, in Proceeding of The Web Conference 2019 (WWW 2019), San Francisco, CA, May 2019 (Research Track, Long Paper). [PDF] [Slides] [Poster] [Code] [arXiv with Erratum]

[15] Xianfeng Tang, Boqing Gong, Yanwei Yu, Huaxiu Yao, Yandong Li, Haiyong Xie, Xiaoyu Wang, Joint Modeling of Dense and Incomplete Trajectories for Citywide Traffic Volume Inference, in Proceeding of The Web Conference 2019 (WWW 2019), San Francisco, CA, May 2019 (Research Track, Long Paper). [PDF] [arXiv]

[16] Huaxiu Yao*, Xianfeng Tang*, Hua Wei, Guanjie Zheng, Zhenhui Li, Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction, in Proceeding of the Thirty-third AAAI Conference on Artificial Intelligence (AAAI 2019), Honolulu, Hawaii, Jan. 2019. [PDF] [Poster] [Code] [Spotlight] [arXiv]

[17] Huaxiu Yao, Defu Lian, Yi Cao, Yifan Wu, Tao Zhou, Predicting Academic Performance for College Students: A Campus Behavior Perspective, ACM Transactions on Intelligent Systems and Technology (TIST) 10.3 (2019): 24. [PDF] [arXiv]

[18] Huaxiu Yao, Fei Wu, Jintao Ke, Xianfeng Tang, Yitian Jia, Siyu Lu, Pinghua Gong, Jieping Ye, Zhenhui Li, Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction, in Proceeding of the Thirty-second AAAI Conference on Artificial Intelligence (AAAI 2018), New Orleans, LA, Feb. 2018. [PDF] [Poster] [Code] [Spotlight] [Penn State News] [arXiv]

[19] Hua Wei, Guanjie Zheng, Huaxiu Yao, and Zhenhui Li, IntelliLight: A Reinforcement Learning Approach for Intelligent Traffic Light Control, in Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2018), London, UK, Aug. 2018 (Research Track). [PDF] [Code] [Demo]

• AI Rising Stars in Chinese Students, Baidu Research, 2021
• College of IST Ph.D. Award for Research Excellence, Penn State University, 2020
• Excellent Bachelor Thesis​ in UESTC, 2016
• Excellent Graduates in UESTC, 2016
• Meritorious Winner in MCM/ICM, 2016 [Report]

Workshop Organization:

• Workshop on Meta-Learning, NeurIPS 2021

Conference Program Committee Member/Reviewer:

• International Conference on Machine Learning (ICML), 2020, 2021
• Annual Conference on Neural Information Processing Systems (NeurIPS), 2020, 2021
• International Conference on Learning Representations (ICLR), 2020, 2021
• ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2020, 2021
• AAAI Conference on Artificial Intelligence (AAAI), 2020, 2021
• International Joint Conferences on Artificial Intelligence (IJCAI), 2020
• Annual Meeting of the Association for Computational Linguistics (ACL), 2021
• International Conference on Information and Knowledge Management (CIKM), 2019

Journal Invited Reviewer:

• IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI)
• Journal of Artificial Intelligence (AIJ)
• ACM Transactions on Knowledge Discovery from Data (TKDD)
• IEEE Transactions on Knowledge and Data Engineering (TKDE)
• ACM Transaction on Intelligent System and Technology (TIST)
• IEEE Transaction on Big Data (TBD)
• IEEE Transactions on Intelligent Transportation Systems (TITS)
• Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT)
• Knowledge and Information Systems (KAIS)

Teaching Assistant, IST 597: Reinforcement Learning, Instructor: Dr. Zihan Zhou, Fall 2019