TY - JOUR
T1 - A Summary of ICDE 2022 Research Session Panels
AU - Bao, Zhifeng
AU - Bouros, Panagiotis
AU - Cheng, Reynold
AU - Choi, Byron
AU - Dignös, Anton
AU - Ding, Wei
AU - Fang, Yixiang
AU - Han, Boyang
AU - Hu, Jilin
AU - Khan, Arijit
AU - Lin, Wenqing
AU - Lin, Xuemin
AU - Long, Cheng
AU - Mamoulis, Nikos
AU - Pei, Jian
AU - Renz, Matthias
AU - Shekhar, Shashi
AU - Shi, Jieming
AU - Zacharatou, Eleni Tzirita
AU - Wang, Sibo
AU - Wang, Xiao
AU - Wang, Xue
AU - Chi-Wing Wong, Raymond
AU - Yan, Da
AU - Yan, Xifeng
AU - Yang, Bin
AU - Yao, Dezhong
AU - Zhang, Ce
AU - Zhao, Peilin
AU - Zhu, Rong
PY - 2023/12
Y1 - 2023/12
N2 - In the 38th IEEE International Conference on Data Engineering (ICDE), 2022, panel discussions were introduced after paper presentations to facilitate in-depth exploration of research topics and encourage participation. These discussions, enriched by diverse perspectives from experts and active audience involvement, provided fresh insights and a broader understanding of each topic. The introduction of panel discussions exceeded expectations, attracting a larger number of participants to the virtual sessions. This article summarizes the virtual panels held during ICDE’22, focusing on sessions such as Data Mining and Knowledge Discovery, Federated Learning, Graph Data Management, Graph Neural Networks, Spatial and Temporal Data Management, and Spatial and Temporal Data Mining. By showcasing the success of panel discussions in generating inspiring discussions and promoting participation, this article aims to benefit the data engineering community, providing a valuable resource for researchers and suggesting a compelling format of holding research sessions for future conferences.
AB - In the 38th IEEE International Conference on Data Engineering (ICDE), 2022, panel discussions were introduced after paper presentations to facilitate in-depth exploration of research topics and encourage participation. These discussions, enriched by diverse perspectives from experts and active audience involvement, provided fresh insights and a broader understanding of each topic. The introduction of panel discussions exceeded expectations, attracting a larger number of participants to the virtual sessions. This article summarizes the virtual panels held during ICDE’22, focusing on sessions such as Data Mining and Knowledge Discovery, Federated Learning, Graph Data Management, Graph Neural Networks, Spatial and Temporal Data Management, and Spatial and Temporal Data Mining. By showcasing the success of panel discussions in generating inspiring discussions and promoting participation, this article aims to benefit the data engineering community, providing a valuable resource for researchers and suggesting a compelling format of holding research sessions for future conferences.
KW - Panel Discussions
KW - Data Engineering
KW - Data Mining
KW - Federated Learning
KW - Graph Neural Networks
KW - Panel Discussions
KW - Data Engineering
KW - Data Mining
KW - Federated Learning
KW - Graph Neural Networks
M3 - Journal article
VL - Vol. 47
JO - {IEEE} Data Engineering Bulletin
JF - {IEEE} Data Engineering Bulletin
IS - 4
ER -