Jianan Zhao

Andy (Jianan) Zhao

I am currently a third-year PhD candidate in Computer Science at Mila and the University of Montreal, supervised by Prof. Jian Tang. Before embarking on my PhD journey, I completed my MSc in Computer Science at Beijing University of Posts and Telecommunications, under the guidance of Prof. Chuan Shi. I am passionate about developing simple yet effective methods and primarily focus my research on graph machine learning and natural language processing.

Email / Github / Google Scholar / Twitter

Selected Publications

(* stands for equal contribution)

Fully-inductive Node Classification on Arbitrary Graphs
Jianan Zhao*, Zhaocheng Zhu*, Mikhail Galkin, Hesham Mostafa, Michael Bronstein, Jian Tang
We propose GraphAny, the first fully-inductive node classification model that generalizes to any graph with arbitrary structure, feature and label spaces. GraphAny surpasses supervised baselines (e.g. GCN, GAT) in an inductive manner.
[ICLR'25], [NeurIPS'24 AFM Workshop]
[paper] [code] [blog]

Position: Graph Foundation Models Are Already Here
Haitao Mao, Zhikai Chen, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, Jiliang Tang
[ICML'24 Spotlight (335/9473)]
[paper]

GraphText: Graph Reasoning in Text Space
Jianan Zhao, Le Zhuo, Yikang Shen, Meng Qu, Kai Liu, Michael Bronstein, Zhaocheng Zhu, Jian Tang
GraphText enables training-free and interactive graph reasoning using LLMs.
[NeurIPS'24 AFM Workshop]
[paper] [code]

Learning on Large-scale Text-attributed Graphs via Variational Inference
Jianan Zhao*, Meng Qu*, Chaozhuo Li, Hao Yan, Qian Liu, Rui Li, Xing Xie, Jian Tang
[ICLR'23 Notable-top5% (Oral)] International Conference on Learning Representations
Top 1 accuracy of three datasets on the Open Graph Benchmark.
[paper] [code]

HousE: Knowledge Graph Embedding with Householder Parameterization
Rui Li, Jianan Zhao, Chaozhuo Li, Di He, Yiqi Wang, Yuming Liu, Hao Sun,
Senzhang Wang, Weiwei Deng, Yanming Shen, Xing Xie, Qi Zhang
[ICML'22] The International Conference of Machine Learning
[paper] [code]

Self-Supervised Graph Structure Refinement for Graph Neural Networks
Jianan Zhao*, Qianlong Wen*, Mingxuan Ju, Chuxu Zhang, Yanfang Ye
[WSDM'23] : ACM International Conference on Web Search and Data Mining
[paper] [code]

Adaptive Kernel Graph Neural Network
Mingxuan Ju, Shifu Hou, Yujie Fan, Jianan Zhao, Liang Zhao, Yanfang Ye
[AAAI'22] AAAI Conference on Artificial Intelligence
[paper] [code]

Gophormer: Ego-Graph Transformer for Node Classification
Jianan Zhao*, Rui Li*, Qianlong Wen*, Chaozhuo Li, Yiqi Wang, Yuming Liu, Hao Sun, Yanfang Ye, Xing Xie
Arxiv Preprint, 2021
[paper] [code]

RxNet: Rx-refill Graph Neural Network for Overprescribing Detection
Jianfei Zhang, Ai-Te Kuo, Jianan Zhao, Qianlong Wen, Erin Winstanley, Chuxu Zhang, Yanfang Ye
[CIKM'21] ACM International Conference on Information and Knowledge Management
Best Full-Paper Award [1/1251]
[paper]

Multi-View Self-Supervised Heterogeneous Graph Embedding
Jianan Zhao*, Qianlong Wen*, Shiyu Sun, Yanfang Ye, Chuxu Zhang
[ECML/PKDD'21] European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
[paper] [code]

Heterogeneous Graph Structure Learning for Graph Neural Networks
Jianan Zhao*, Xiao Wang*, Chuan Shi, Binbin Hu, Guojie Song, Yanfang Ye
[AAAI'21] AAAI Conference on Artificial Intelligence
[paper] [code]

Network Schema Preserving Heterogeneous Information Network Embedding
Jianan Zhao*, Xiao Wang*, Chuan Shi, Zekuan Liu, Yanfang Ye
[IJCAI'20] International Joint Conference on Artificial Intelligence
[paper] [code]