A Summary of ICDE 2022 Research Session Panels

Zhifeng  Bao; Panagiotis  Bouros; Reynold  Cheng; Byron  Choi; Anton  Dignös; Wei  Ding; Yixiang  Fang; Boyang  Han; Jilin  Hu; Arijit  Khan; Wenqing  Lin; Xuemin  Lin; Cheng  Long; Nikos  Mamoulis; Jian  Pei; Matthias  Renz; Shashi  Shekhar; Jieming  Shi; Eleni Tzirita Zacharatou; Sibo  Wang; Xiao  Wang; Xue  Wang; Raymond  Chi-Wing Wong; Da  Yan; Xifeng  Yan; Bin  Yang; Dezhong  Yao; Ce  Zhang; Peilin  Zhao; Rong  Zhu

A Summary of ICDE 2022 Research Session Panels

Zhifeng Bao
, Panagiotis Bouros
, Reynold Cheng
, Byron Choi
, Anton Dignös
, Wei Ding
, Yixiang Fang
, Boyang Han
, Jilin Hu
, Arijit Khan
, Wenqing Lin
, Xuemin Lin
, Cheng Long
, Nikos Mamoulis
, Jian Pei
, Matthias Renz
, Shashi Shekhar
, Jieming Shi
, Eleni Tzirita Zacharatou
, Sibo Wang

Xiao Wang, Xue Wang, Raymond Chi-Wing Wong, Da Yan, Xifeng Yan, Bin Yang, Dezhong Yao, Ce Zhang, Peilin Zhao, Rong Zhu

Data-intensive Systems and Applications

Alibaba Group
University of Massachusetts
University of New South Wales
Simon Fraser University
Saint Mary's University of Minnesota
University of California
Aalborg Universitet
Chinese University of Hong Kong
Beijing University of Posts and Telecommunications
Johannes Gutenberg University Mainz
Free University of Bozen-Bolzano
University of Ioannina
Christian-Albrechts-Universitetet
Royal Melbourne Institute of Technology (RMIT)
Nanyang Technological University
ETH Zürich
Tencent AI Lab
Hong Kong Baptist University
Chinese University of Hong Kong, Shenzhen
JD Intelligent Cities Research
Tencent
The Hong Kong Polytechnic University, School of Design
The University of Hong Kong
Huazhong University of Science and Technology
Indiana University
Hong Kong University of Science and Technology

Publikation: Artikel i tidsskrift og konference artikel i tidsskrift › Tidsskriftartikel › Formidling

Abstract

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.

Originalsprog	Engelsk
Tidsskrift	{IEEE} Data Engineering Bulletin
Vol/bind	Vol. 47
Udgave nummer	4
Status	Udgivet - dec. 2023

Emneord

Panel Discussions
Data Engineering
Data Mining
Federated Learning
Graph Neural Networks

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http://sites.computer.org/debull/A23dec/p4.pdfLicens: CC BY-ND

Citationsformater

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title = "A Summary of ICDE 2022 Research Session Panels",

abstract = "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{\textquoteright}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.",

keywords = "Panel Discussions, Data Engineering, Data Mining, Federated Learning, Graph Neural Networks, Panel Discussions, Data Engineering, Data Mining, Federated Learning, Graph Neural Networks",

author = "Zhifeng Bao and Panagiotis Bouros and Reynold Cheng and Byron Choi and Anton Dign{\"o}s and Wei Ding and Yixiang Fang and Boyang Han and Jilin Hu and Arijit Khan and Wenqing Lin and Xuemin Lin and Cheng Long and Nikos Mamoulis and Jian Pei and Matthias Renz and Shashi Shekhar and Jieming Shi and Zacharatou, \{Eleni Tzirita\} and Sibo Wang and Xiao Wang and Xue Wang and \{Chi-Wing Wong\}, Raymond and Da Yan and Xifeng Yan and Bin Yang and Dezhong Yao and Ce Zhang and Peilin Zhao and Rong Zhu",

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month = dec,

language = "English",

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journal = "\{IEEE\} Data Engineering Bulletin",

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Bao, Z, Bouros, P, Cheng, R, Choi, B, Dignös, A, Ding, W, Fang, Y, Han, B, Hu, J, Khan, A, Lin, W, Lin, X, Long, C, Mamoulis, N, Pei, J, Renz, M, Shekhar, S, Shi, J, Zacharatou, ET, Wang, S, Wang, X, Wang, X, Chi-Wing Wong, R, Yan, D, Yan, X, Yang, B, Yao, D, Zhang, C, Zhao, P & Zhu, R 2023, 'A Summary of ICDE 2022 Research Session Panels', {IEEE} Data Engineering Bulletin, bind Vol. 47, nr. 4. <http://sites.computer.org/debull/A23dec/p4.pdf>

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 -

A Summary of ICDE 2022 Research Session Panels

Abstract

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