您现在的位置是: 赵康菲

国家级高层次人才

姓名:赵康菲
所在学科:
职称:准聘教授
联系电话:13040856399
E-mail:zkf1105@gmail.com
通信地址:

个人信息

赵康菲,北京理工大学准聘教授、博士生导师,入选国家高层次人才。2014于中国科学技术大学永利皇宫463cc获工学学士学位,2019年于香港中文大学系统工程与工程管理学系获博士学位。2023年加入北京理工大学,此前先后于香港中文大学担任博士后研究员、腾讯人工智能实验室(Tencent AI Lab)担任高级研究员。主要研究方向为数据库、数据挖掘、人工智能。已发表计算机学会(CCF)推荐A类论文近20篇,其中包括数据库及数据挖掘领域顶级会议ACM SIGMOD、VLDB、ICDE, NeurIPS, 以及顶级期刊VLDB Journal、TKDE等。

News: 每年计划招收博士生1名,硕士生2-3名,同时也欢迎对科研感兴趣的高年级本科生加入实验室。

个人主页:https://kangfei.github.io


科研方向

ML/DL for Graphs and Database System, In-Databases ML

Graph Analytics, Graph Data Management, Graph Algorithms


代表性学术成果

· Shuheng Fang, Kangfei Zhao*, Guanghua Li, Jeffrey Xu Yu. Community Search: A Meta-Learning Approach IEEE ICDE 2023

· Kangfei Zhao, Jeffrey Xu Yu, Qiyan Li, Hao Zhang, Yu Rong. Learned Sketch for Subgraph Counting: A Holistic Approach. Springer VLDB Journal 2023

· Kangfei Zhao, Jeffrey Xu Yu, Zongyan He, Rui Li, Hao Zhang. Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process. ACM SIGMOD 2022

· Kangfei Zhao, Jeffrey Xu Yu, Hao Zhang, Qiyan Li, Yu Rong. A Learned Sketch for Subgraph Counting. ACM SIGMOD 2021

· Kangfei Zhao, Zhiwei Zhang, Yu Rong, Jeffrey Xu Yu, Junzhou Huang. Finding Critical Users in Social Communities via Graph Convolutions. IEEE Trans. on Know. and Data Eng. (TKDE), 2021

· Kangfei Zhao, Jiao Su, Jeffrey Xu Yu, Hao Zhang. SQL-G: An SQL Approach For Graph Analytics on Distributed Graph Processing Systems. IEEE Trans. on Know. and Data Eng. (TKDE) 2019

· Kangfei Zhao and Jeffrey Xu Yu. All-in-One: Graph Processing in RDBMSs Revisited. ACM SIGMOD 2017

· Kangfei Zhao and Jeffrey Xu Yu. Graph Processing in RDBMSs. IEEE Data Engineering Bulletin 2017


承担科研情况

所获奖励

NeurIPS 2022 Open Catalyst Challenge, 1st Winner, 2022

Google China Anita Borg Scholarship (30 in China Mainland) , 2013


社会兼职

程序委员:DASFAA’20, DASFAA’23, WSDM’22, PAKDD’21, PAKDD’22, VLDB’22, VLDB’24, KDD’22, KDD’23 CIKM’22, ICDE’23

审稿人:EEE TKDE, IEEE TPAMI, Information Science


备注

DBLP: https://dblp.org/pid/169/1501.html

Google Scholar: https://scholar.google.com/citations?user=ZPCRhOsAAAAJ&hl=en