VLDB 2022: Conference Awards

Chaired by Xuemin Lin and Fatma Ozcan

Best Regular Research Paper

Sancus: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks Jingshu Peng (Hong Kong University of Science and Technology)*, Zhao Chen (Hong Kong University of Science and Technology), Yingxia Shao (BUPT), Yanyan Shen (Shanghai Jiao Tong University), Lei Chen (Hong Kong University of Science and Technology), Jiannong Cao (The Hong Kong Polytechnic University)

Best Regular Research Paper Runner Ups

Threshold Queries in Theory and in the Wild Angela Bonifati (Univ. of Lyon), Stefania Dumbrava (ENSIIE), George Fletcher (Eindhoven University of Technology), Jan Hidders (University of London, Birbeck), Matthias Hofer (University of Bayreuth), Wim Martens (University of Bayreuth), Filip Murlak (University of Warsaw), Joshua Shinavier (Uber), Sławek Staworko (University of Lille)*, Dominik Tomaszuk (University of Bialystok)

Sortledton: a universal, transactional graph data structure Per Fuchs (TU Munich)*, Jana Giceva (TU Munich), Domagoj Margan (Imperial College London)

Best Experiment, Analysis and Benchmark Paper

Accurate Summary-based Cardinality Estimation Through the Lens of Cardinality Estimation Graphs Jeremy Chen (University of Waterloo)*, Yuqing Huang (University of Waterloo), Mushi Wang (University of Waterloo), Semih Salihoglu (University of Waterloo), Kenneth Salem (University of Waterloo)

Best Scalable Data Science Paper

HET: Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework Xupeng Miao (Peking University)*, Hailin Zhang (Peking University), Yining Shi (Peking University), Xiaonan Nie (Peking University), Zhi Yang (Peking University), Yangyu Tao (Tencent), Bin Cui (Peking University)

Best Industry Paper

Hardware Acceleration of Compression and Encryption in SAP HANA Monica Chiosa (ETH Zurich)*, Fabio Maschi (ETH Zurich), Ingo Müller (Google), Gustavo Alonso (ETH Zurich), Norman May (SAP SE)

VLDB2022 Best Demonstration

Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem Yuki Asada (Microsoft), Victor Fu (Microsoft), Apurva Gandhi (Microsoft), Advitya Gemawat (Microsoft), Lihao Zhang (Microsoft), Dong He (the University of Washington), Vivek Gupta (Microsoft), Ehi Nosakhare (Microsoft), Dalitso Banda (Microsoft), Rathijit Sen (Microsoft), and Matteo Interlandi (Microsoft)*

Distinguished Associate Editors

Sourav S Bhowmick
Khuzaima Daudjee
Arun Kumar
Dan Suciu
Wenjie Zhang

Distinguished Reviewers

Matthias Boehm
Aline Bessa
Carsten Binnig
Raymond Chi-Wing Wong
Carlo Curino
Karima Echihabi
Raul Castro Fernandez
Torsten Grust
Yeye He
Pinar Karagoz
Arijit Khan
Matteo Lissandrini
Ioana Manolescu
Umar Farooq Minhas
Davide Mottin
Faisal Nawab
Thomas Neumann
George Papadakis
Tilmann Rabl
Sayan Ranu
Mohamed Sadoghi
Semih Salihoglu
Carlos Scheidegger
Yufei Tao
Yongxin Tong
Eleni Tzirita Zacharatou
Dana van Aken
Ye Yuan