邝炜瑞, Weirui Kuang‘s Resume
邝炜瑞, Weirui Kuang
邝炜瑞, Weirui Kuang
邝炜瑞, Weirui Kuang
E-mail: weiruikuang@gmail.com
@ALIBABA GROUP @DAMO ACADEMY
About Me
Welcome to my homepage! I am a researcher at DAMO Academy, Alibaba Group. I received a B.S. degree in Applied Mathematics and M.E. degree in Computer Applications Technology from Renmin University of China in 2018 and 2021, respectively. My research interests include graph representation learning and federated learning. I have published several papers in KDD, NeurIPS, and VLDB and served as the reviewer for top-tier conferences such as KDD, NeurIPS, ICML, and WWW.
Experience
Alibaba DAMO Academy
- Machine Learning Engineer • June 2021 — Present
- Federated Learning, AutoML, LLM, Graph Represent Learning, etc.
Alibaba DAMO Academy
- Research Intern • April 2021 — June 2021
- Graph Represent Learning, KDD Cup 2021 OGB-LSC 9th
Alibaba Cloud
- Research Intern • March 2020 — March 2021
- Block Storage Cardinality Estimation
Education
Renmin University of China
- Postgrad. in School of Information • 2018 — 2021
- Major in Computer Science and Technology, Graph Learning
- Advisor: Zhewei Wei
Renmin University of China
- B.S. in School of Information • 2014 — 2018
- Major in Mathematics and Applied Mathematics
Scholar Links
Social Links
Publications
Authors marked with * are co-first authors.
Authors marked with † have equal contributions listed in alphabetical order.
2023
- To appear in ICML 2023 - Zhen Wang*, Weirui Kuang*, Ce Zhang, Bolin Ding, Yaliang Li. “FedHPO-Bench: A Benchmark Suite for Federated Hyperparameter Optimization”
- To appear in VLDB 2023 - Xie, Yuexiang*, Zhen Wang*, Dawei Gao, Daoyuan Chen†, Liuyi Yao†, Weirui Kuang†, Yaliang Li, Bolin Ding and Jingren Zhou. “FederatedScope: A Comprehensive and Flexible Federated Learning Platform via Message Passing”
2022
- NeurIPS 2022 - Daoyuan Chen, Dawei Gao, Weirui Kuang, Yaliang Li, Bolin Ding. “pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning”
- KDD 2022, ADS Best Paper - Zhen Wang, Weirui Kuang, Yuexiang Xie, Liuyi Yao, Yaliang Li, Bolin Ding, Jingren Zhou. “FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning”
- KDD 2022 - Zhen Wang, Yaliang Li, Zhewei Wei, Weirui Kuang, Bolin Ding. “Graph Neural Networks with Nodewise Architecture”
News
2023
- April 25th: Congratulations! My co-first-authored paper “FedHPO-Bench: A Benchmark Suite for Federated Hyperparameter Optimization” has been accepted by ICML!!!
- April 20th: A new personal homepage is built.
2022
- August 18th: FS-GNN wins the Best Paper Award on [KDD 2022 ADS Track]!!!
- May 19th: Congratulations! “FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning” has been accepted by KDD!!!
- March 30th: FederatedScope is open source now! Try at try.federatedscope.io!