ACM SIGMOD City, Country, Year
sigmod pods logo




SIGMOD 2021: Accepted Research Papers

  • LIMA: Fine-grained Lineage Tracing and Reuse in Machine Learning Systems
    Arnab Phani (Graz University of Technology)*; Benjamin Rath (TU Graz); Matthias Boehm (Graz University of Technology)
  • Conformance Constraint Discovery: Measuring Trust in Data-Driven Systems
    Anna Fariha (University of Massachusetts Amherst)*; Ashish Tiwari (Microsoft); Arjun Radhakrishna (Microsoft); Sumit Gulwani (Microsoft Research); Alexandra Meliou (University of Massachusetts Amherst)
  • Multiple Dynamic Outlier-Detection from a Data Stream by Exploiting Duality of Data and Queries
    Susik Yoon (KAIST); Yooju Shin (KAIST); Jae-Gil Lee (KAIST)*; Byung Suk Lee (University of Vermont)
  • Why Not Match: On Explanations of Event Pattern Queries
    Shaoxu Song (Tsinghua University)*; Ruihong Huang (Tsinghua University); Yu Gao (Tsinghua University); Jianmin Wang ("Tsinghua University, China")
  • Online Topic-Aware Entity Resolution Over Incomplete Data Streams
    Weilong Ren (Kent State University); Xiang Lian (Kent State University)*; Kambiz Ghazinour (Kent state university)
  • Auto-Validate: Unsupervised Data Validation Using Data-Domain Patterns Inferred from Data Lakes
    Jie Song (University of Michigan); Yeye He (Microsoft Research)*
  • ReStore - Neural Data Completion for Relational Databases
    Benjamin Hilprecht (TU Darmstadt)*; Carsten Binnig (TU Darmstadt)
  • On Saving Outliers for Better Clustering over Noisy Data
    Shaoxu Song (Tsinghua University)*; Fei Gao (Tsinghua University); Ruihong Huang (Tsinghua University); Yihan Wang (Tsinghua University)
  • Looking for Trouble: Analyzing Classifier Behavior via Pattern Divergence
    Eliana Pastor (Politecnico di Torino)*; Luca de Alfaro (University of California, Santa Cruz); Elena Baralis (Dipartimento di Automatica e Informatica Politecnico di Torino)
  • Shahin: Faster Algorithms for Generating Explanations for Multiple Predictions
    Sona Hasani (Google); Saravanan Thirumuruganathan (QCRI)*; Nick Koudas (University of Toronto); Gautam Das (U. of Texas Arlington)
  • REDS: Rule Extraction for Discovering Scenarios
    Vadim Arzamasov (Karlsruhe Institute of Technology)*; Klemens Böhm (Karlsruhe Institute of Technology (KIT))
  • VeriDB: An SGX-based Verifiable Database
    Wenchao Zhou (Georgetown University)*; Yifan Cai (University of Pennsylvania); Yanqing Peng (University of Utah); Sheng Wang (Alibaba Group); Ke Ma (Shanghai Jiaotong University); Feifei Li (Alibaba Group)
  • Properties of Inconsistency Measures for Databases
    Ester Livshits (Technion)*; Rina Kochirgan (Technion); Segev Tsur (Technion); Ihab F Ilyas (U. of Waterloo); Benny Kimelfeld (Technion); Sudeepa Roy (Duke University, USA)
  • FastVer: Making Data Integrity a Commodity
    Arvind Arasu (Microsoft)*; Badrish Chandramouli (Microsoft Research); Johannes Gehrke (Microsoft); Esha Ghosh (Microsoft); Donald Kossmann (Microsoft Research); Jonathan Protzenko (Microsoft); Ravi Ramamurthy (MICROSOFT); Tahina Ramananandro (Microsoft); Aseem Rastogi (Microsoft); Srinath Setty (Microsoft Research); Nikhil Swamy (Microsoft); Alexander van Renen (TUM); Min Xu (University of Chicago)
  • Identifying Insufficient Data Coverage for Ordinal Continuous-Valued Attributes
    Abolfazl Asudeh (University of Illinois at Chicago)*; Nima Shahbazi (University of Illinois at Chicago); Zhongjun Jin (University of Michigan); H. V. Jagadish (University of Michigan)
  • Structural Generalizability: The Case of Similarity Search
    Yodsawalai Chodpathumwan (University of Illinois); Arash Termehchy (Oregon State University)*; Stephen Ramsey (Oregon State University); Aayam Shrestha (Oregon State University); Amy Glen (Oregon State University); Zheng Liu (Oregon State University)
  • Adaptive Rule Discovery for Labeling Text Data
    Sainyam Galhotra (University of Massachusetts Amherst)*; Behzad Golshan (Megagon Labs); Wang-Chiew Tan (Facebook AI)
  • Rethink the Scan in MVCC Databases
    Jongbin Kim (Hanyang University); Kihwang Kim (Hanyang University); Hyunsoo Cho (Hanyang University); Jaeseon Yu (Hanyang University); Sooyong Kang (Hanyang University); Hyungsoo Jung (Hanyang University)*
  • Blockchains vs. Distributed Databases: Dichotomy and Fusion
    Pingcheng Ruan (National University of Singapore); Tien Tuan Anh Dinh (Singapore University of Technology and Design); Dumitrel Loghin (National University of Singapore); Meihui Zhang (Beijing Institute of Technology)*; Gang Chen (Zhejiang University); Qian Lin (ByteDance); Beng Chin Ooi (NUS)
  • SharPer: Sharding Permissioned Blockchains Over Network Clusters
    Mohammad Javad Amiri (University of Pennsylvania)*; Divy Agrawal (University of California, Santa Barbara); Amr El Abbadi (UC Santa Barbara)
  • Why Do My Blockchain Transactions Fail? A Study of Hyperledger Fabric
    Jeeta Ann Chacko (Technical University of Munich)*; Ruben Mayer (Technical University of Munich); Hans-Arno Jacobsen (TUM)
  • Do the Rich Get Richer? Fairness Analysis for Blockchain Incentives
    YUMING HUANG (National University of Singapore); Jing Tang (National University of Singapore)*; Qianhao Cong (National University of Singapore); Andrew Lim (National University of Singapore); Jianliang Xu (Hong Kong Baptist University)
  • Releasing Locks As Early As You Can: Reducing Contention of Hotspots by Violating Two-Phase Locking
    Zhihan Guo (University of Wisconsin-Madison)*; Kan Wu (University of Wisconsin-Madison); cong yan (Microsoft Research); Xiangyao Yu (University of Wisconsin-Madison)
  • P^2B-Trace: Privacy-Preserving Blockchain-based Contact Tracing to Combat Pandemics
    Zhe PENG (Hong Kong Baptist University)*; Cheng Xu (Hong Kong Baptist University); Haixin Wang (HKBU); Jinbin Huang (Hong Kong Baptist University); Jianliang Xu (Hong Kong Baptist University); Xiaowen Chu (Hong Kong Baptist University)
  • Clonos: Consistent Causal Recovery for Highly-Available Streaming Dataflows
    Pedro Silvestre (TU Delft); Marios Fragkoulis (TU Delft)*; Diomidis Spinellis (TU Delft); Asterios Katsifodimos (TU Delft)
  • Parallelizing Intra-Window Join on Multicores: An Experimental Study
    Shuhao Zhang (Singapore University of Technology and Design)*; Yancan Mao (National University of Singapore); Jiong He (A*Star); Philipp Marian Grulich (Technische Universität Berlin); Steffen Zeuch (Humboldt Universität zu Berlin); Bingsheng He (National University of Singapore); Richard T.B. Ma (National University of Singapore); Volker Markl (Technische Universität Berlin)
  • An In-Depth Benchmarking of Text-to-SQL Systems
    Orest Gkini (Athena Research Center); Theofilos Belmpas (Athena Research Center); Georgia Koutrika (Athena Research Center)*; Yannis Ioannidis (University of Athens)
  • Synthesizing Linked Data Under Cardinality and Integrity Constraints
    Amir Gilad (Duke University)*; Shweta Patwa (Duke University); Ashwin Machanavajjhala (Duke)
  • Towards Benchmarking Feature Type Inference for AutoML Platforms
    Vraj Shah (University of California, San Diego)*; Jonathan Lacanlale (California State University, Northridge); Premanand Kumar (University of California, San Diego); Kevin Yang (University of California, San Diego); Arun Kumar (University of California, San Diego)
  • Reducing Ambiguity in Json Schema Discovery
    William Spoth (University at Buffalo)*; Oliver A Kennedy (University at Buffalo, SUNY); Ying Lu (Oracle); Beda Hammerschmidt (Oracle); Zhen Hua Liu (Oracle)
  • Auto-FuzzyJoin: Auto-Program Fuzzy Similarity Joins Without Labeled Examples
    Peng Li (GATECH); Xiang Cheng (GATECH); Xu Chu (GATECH); Yeye He (Microsoft Research)*; Surajit Chaudhuri (Microsoft)
  • Joint Open Knowledge Base Canonicalization and Linking
    Yinan Liu (Nankai University)*; Wei Shen (Nankai University); Yuanfei Wang (Nankai University); Jianyong Wang (Tsinghua University); Zhenglu Yang (Nankai University); Xiaojie Yuan (Nankai Univeristy)
  • BullFrog: Online Schema Evolution via Lazy Evaluation
    Souvik Bhattacherjee (University of Maryland, College Park); GANG LIAO (UNIVERSITY OF MARYLAND); Michael Hicks (University of Maryland, College Park); Daniel J Abadi (UMD)*
  • Medical Entity Disambiguation using Graph Neural Networks
    Alina Vretinaris (IBM Germany); Chuan Lei (IBM Research - Almaden)*; Vasilis Efthymiou (FORTH-ICS); Xiao Qin (IBM Research); Fatma Ozcan (Google)
  • TENET: Joint Entity and Relation Linking with Coherence Relaxation
    Xueling Lin (Hong Kong University of Science and Technology)*; Lei Chen (Hong Kong University of Science and Technology); Chaorui Zhang (Huawei)
  • Allign: Aligning All-Pair Near-Duplicate Passages in Long Texts
    Dong Deng (Rutgers Universituy - New Brunswick)*
  • Out of Many We are One: Measuring Item Batch with Clock-Sketch
    Peiqing Chen (Peking University); Dong Chen (Peking University); Lingxiao Zheng (Peking University); Jizhou Li (Peking University); Tong Yang (Peking University)*
  • JSON Tiles: Fast Analytics on Semi-Structured Data
    Dominik Durner (TUM)*; Viktor Leis ( Friedrich-Alexander-Universität Erlangen-Nürnberg); Thomas Neumann (TUM)
  • BurstSketch: Finding Bursts in Data Streams
    Zheng Zhong (Peking University)*; Shen Yan (Peking University); Zikun Li (Peking University); Decheng Tan (Peking University); Tong Yang (Peking University); Bin Cui (Peking University)
  • Building Fast and Compact Sketches for Approximately Multi-Set Multi-Membership Querying
    Rundong Li (Xi'an Jiaotong University)*; Pinghui Wang (Xi'an Jiaotong University); Jiongli Zhu (Xi'an Jiaotong University); Junzhou Zhao (Xi'an Jiaotong University); Jia Di (Xi'an Jiaotong University); Xiaofei Yang (Xi'an Jiaotong University); Kai Ye (Xi'an Jiaotong University)
  • Bidirectionally Densifying LSH Sketches with Empty Bins
    Peng Jia (Xi'an Jiaotong University)*; Pinghui Wang (Xi'an Jiaotong University); Junzhou Zhao (Xi'an Jiaotong University); Shuo Zhang (Xi'an Jiaotong University); Yiyan Qi (Xi'an Jiaotong University); Min Hu (China Mobile Research Institute); Chao Deng (China Mobile Research Institute); Xiaohong Guan (Xi'an Jiaotong University)
  • Minimizing the Regret of an Influence Provider
    Yipeng Zhang (RMIT University); Yuchen Li (Singapore Management University); Zhifeng Bao (RMIT University)*; Baihua Zheng (Singapore Management University); H. V. Jagadish (University of Michigan)
  • Fast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering
    Yiqiu Wang (Massachusetts Institute of Technology)*; Shangdi Yu (Massachusetts Institute of Technology); Yan Gu (UC Riverside); Julian Shun (MIT)
  • A Generalized Approach for Reducing Expensive Distance Calls for A Broad Class of Proximity Problems
    Jees Augustine (The University of Texas at Arlington)*; Suraj Shetiya (The University of Texas at Arlington); Mohammadreza Esfandiari (NJIT); Senjuti Basu Roy (New Jersey Institute of Technology); Gautam Das (U. of Texas Arlington)
  • OmniFair: A Declarative System for Model-Agnostic Group Fairness in Machine Learning
    Hantian Zhang (Georgia Tech)*; Xu Chu (GATECH); Abolfazl Asudeh (University of Illinois at Chicago); Shamkant Navathe (GaTech)
  • Slice Tuner: A Selective Data Acquisition Framework for Accurate and Fair Machine Learning Models
    KIHYUN TAE (KAIST); Steven Whang (KAIST)*
  • EquiTensors: Learning Fair Integrations of Heterogeneous Urban Data
    An Yan (University of Washington)*; Bill G Howe (University of Washington)
  • Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals
    Sainyam Galhotra (University of Massachusetts Amherst)*; Romila Pradhan (University of California San Diego); Babak Salimi (Unievristy of California at San Diego)
  • Enforcing Constraints for Machine Learning Systems via Declarative Feature Selection: An Experimental Study
    Felix Neutatz (TU Berlin)*; Felix Biessmann (Einstein Center Digital Future); Ziawasch Abedjan (Leibniz Universität Hannover)
  • Learned Cardinality Estimation for Similarity Queries
    Ji Sun (Tsinghua University); Guoliang Li (Tsinghua University)*; Nan Tang (Qatar Computing Research Institute, HBKU)
  • Scalable Multi-Query Execution using Reinforcement Learning
    Panagiotis Sioulas (EPFL)*; Anastasia Ailamaki (EPFL)
  • A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation
    Peizhi Wu (Nanyang Technological University)*; Gao Cong (Nanyang Technological Univesity)
  • Bao: Making Learned Query Optimization Practical
    Ryan C Marcus (MIT)*; Parimarjan Negi (MIT CSAIL); Hongzi Mao (MIT CSAIL); Nesime Tatbul (Intel Labs and MIT); Mohammad Alizadeh (MIT CSAIL); Tim Kraska (MIT)
  • Rotom: A Meta-Learned Data Augmentation Framework for Entity Matching, Data Cleaning, Text Classification, and Beyond
    Zhengjie Miao (Duke University)*; Yuliang Li (Megagon Labs); Xiaolan Wang (Megagon Labs)
  • SIA: Optimizing Queries using Learned Predicates
    Qi Zhou (Georgia Institute of Technology)*; Joy Arulraj (Georgia Tech); Shamkant Navathe (Georgia Institute of Technology); William Harris (Galois Inc); jinpeng wu (Alibaba)
  • MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems
    Lin Ma (Carnegie Mellon University)*; William Zhang (Carnegie Mellon University); Jie Jiao (Carnegie Mellon University); Wuwen Wang (Carnegie Mellon University); Matthew Butrovich (Carnegie Mellon University); Wan Shen Lim (Carnegie Mellon University); Prashanth Menon (Carnegie Mellon Universiy); Andrew Pavlo (Carnegie Mellon University)
  • Expand your Training Limits! Generating Training Data for ML-based Data Management
    Francesco Ventura (Politecnico di Torino)*; Zoi Kaoudi (TU Berlin); Jorge Arnulfo Quiane Ruiz (TU Berlin); Volker Markl (Technische Universität Berlin)
  • ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases
    Xinyi Zhang (Peking University); HONG WU (Alibaba); Zhuo Chang (Peking University); Shuowei Jin (Alibaba Group); Jian Tan (Alibaba); Feifei Li (Alibaba Group); Tieying Zhang (Alibaba Group); Bin Cui (Peking University)*
  • Efficient Deep Learning Pipelines for Accurate Cost Estimations Over Large Scale Query Workload
    Johan Zhi Kang Kok (Grab)*; Gaurav Gaurav (Grab); Sienyi Tan (Grab); Feng Cheng (Grab); Shixuan Sun (National University of Singapore); Bingsheng He (National University of Singapore)
  • Towards Enhancing Database Education: Natural Language Generation Meets Query Execution Plans
    Weiguo Wang (Xidian University); Sourav S Bhowmick (Nanyang Technological University)*; Hui Li (Xidian University); Shafiq Joty (Nanyang Technological University); Siyuan Liu (Nanyang Technological University); Peng Chen (Xidian University)
  • To not miss the forest for the trees - A holistic approach for explaining missing answers over nested data
    Ralf Diestelkämper (University of Stuttgart); Seokki Lee (University of Cincinnati); Melanie Herschel (Universität Stuttgart); Boris Glavic (Illinois Institute of Technology)*
  • Putting Things into Context: Rich Explanations for Query Answers using Join Graphs
    Chenjie Li (Illinois Institute of Technology ); Zhengjie Miao (Duke University); Qitian Zeng (Illinois Institute of Technology); Boris Glavic (Illinois Institute of Technology)*; Sudeepa Roy (Duke University, USA)
  • Pool of Experts: Realtime Querying Specialized Knowledge in Massive Neural Networks
    Hakbin Kim (Inha University); Dong-Wan Choi (Inha University)*
  • Scalable and Usable Relational Learning With Automatic Language Bias
    Jose Picado (Oregon State University); Arash Termehchy (Oregon State University)*; Alan Fern (Oregon State University); Sudhanshu Pathak (Oregon State University); Praveen Ilango (Oregon State University); John Davis (Oregon State University)
  • Marrying Top-k with Skyline Queries: Relaxing the Preference Input while Producing Output of Controllable Size
    Kyriakos Mouratidis (Singapore Management University)*; Keming Li (Southern University of Science and Technology); Bo Tang (Southern University of Science and Technology)
  • Proportionality in Spatial Keyword Search
    Georgios Kalamatianos (Uppsala University); George Fakas (Uppsala University)*; Nikos Mamoulis (University of Ioannina)
  • Boosting Graph Similarity Search through Pre-computation
    Jongik Kim (Jeonbuk National University)*
  • Sliding Window-based Approximate Triangle Counting over Streaming Graphs with Duplicate Edges
    Xiangyang Gou (Peking University); Lei Zou (Peking University)*
  • Accelerating Triangle Counting on GPU
    Lin Hu (Peking University); Lei Zou (Peking University)*; Yu Liu (Peking University)
  • Graph Iso/Auto-morphism: A Divide-&-Conquer Approach
    Can Lu (The Chinese University of Hong Kong)*; Jeffrey Xu Yu (Chinese University of Hong Kong); Zhiwei Zhang (Hong Kong Baptist University); Hong Cheng (Chinese University of Hong Kong)
  • Query-by-Sketch: Scaling Shortest Path Graph Queries on Very Large Networks
    Ye Wang (Australian National University)*; Qing Wang (ANU); Henning Koehler (Massey University); Yu Lin (Australian National University)
  • Graphsurge: Graph Analytics on View Collections Using Differential Computation
    Siddhartha Sahu (University of Waterloo)*; Semih Salihoglu (University of Waterloo)
  • Combining Sampling and Synopses with Worst-Case Optimal Runtime And Quality Guarantees for Graph Pattern Cardinality Estimation
    Kyoungmin Kim (POSTECH); Hyeonji Kim (POSTECH); George Fletcher (Eindhoven University of Technology); Wook-Shin Han (POSTECH)*
  • Versatile Equivalences: Speeding up Subgraph Query Processing and Subgraph Matching
    Hyunjoon Kim (Seoul National University); Yunyoung Choi (Seoul National University); Kunsoo Park (Seoul National University); Xuemin Lin (University of New South Wales); Seok-Hee Hong (The University of Sydney); Wook-Shin Han (POSTECH)*
  • Efficient Exact Algorithms for Maximum Balanced Biclique Search in Bipartite Graphs
    Lu Chen (Swinburne University of Technology)*; Chengfei Liu (Swinburne University of Technology); Rui Zhou (Swinburne University of Technology); Jiajie Xu (Soochow University); Jianxin Li (Deakin University)
  • Parallel Index-Based Structural Graph Clustering and Its Approximation
    Tom Tseng (Massachusetts Institute of Technology)*; Laxman Dhulipala (MIT CSAIL); Julian Shun (MIT)
  • Self-adaptive Graph Traversal on GPUs
    Mo Sha (National University of Singapore)*; Yuchen Li (Singapore Management University); Kian-Lee Tan (National University of Singapore)
  • Efficient and Effective Algorithms for Revenue Maximization in Social Advertising
    Kai Han (University of Science and Technology of China)*; Benwei Wu (University of Science and Technology of China); Jing Tang (National University of Singapore); Shuang Cui (University of Science and Technology of China); Cigdem Aslay (Aarhus University); Laks V.S. Lakshmanan (The University of British Columbia)
  • Unifying the Global and Local Approaches: An Efficient Power Iteration with Forward Push
    Hao Wu (University of Melbourne); Junhao Gan (University of Melbourne)*; Zhewei Wei (Renmin University of China); Rui Zhang (" University of Melbourne, Australia")
  • Imminence Monitoring of Critical Events: A Representation Learning Approach
    Yan Li (University of Massachusetts, Lowell); Tingjian Ge (University of Massachusetts, Lowell)*
  • Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce
    Xupeng Miao (Peking University)*; Xiaonan Nie (Peking University); Yingxia Shao (BUPT); Zhi Yang (Peking University); Jiawei Jiang (ETH Zurich); Lingxiao Ma (Peking University); Bin Cui (Peking University)
  • Hybrid Evaluation for Distributed Iterative Matrix Computation
    Zihao Chen (East China Normal University); Chen Xu (East China Normal University)*; Juan Soto (TU Berlin); Volker Markl (Technische Universität Berlin); Weining Qian (East China Normal University); Aoying Zhou (East China Normal University )
  • SliceLine: Fast, Linear-Algebra-based Slice Finding for ML Model Debugging
    Svetlana Sagadeeva (Graz University of Technology); Matthias Boehm (Graz University of Technology)*
  • HedgeCut: Maintaining Randomized Trees for Low-Latency Machine Unlearning
    Sebastian Schelter (University of Amsterdam)*; Stefan Grafberger (TU Munich); Ted Dunning (MapR Technologies)
  • VF^2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning
    Fangcheng Fu (Peking University)*; Yingxia Shao (BUPT); Lele Yu (Peking University); Jiawei Jiang (ETH Zurich); Huanran Xue (Tencent Inc.); Yangyu Tao (Tencent); Bin Cui (Peking University)
  • ALG: Fast and Accurate Active Learning Framework for Graph Convolutional Networks
    Wentao Zhang (Peking University)*; Yu Shen (Peking University); Yang Li (Peking University); Lei Chen (Hong Kong University of Science and Technology); Zhi Yang (Peking University); Bin Cui (Peking University)
  • Towards Demystifying Serverless Machine Learning Training
    Jiawei Jiang (ETH Zurich)*; Shaoduo Gan (ETH Zurich); Yue Liu (ETH Zurich); Fanlin Wang (ETHZ); Gustavo Alonso (ETHZ); Ana Klimovic (ETH Zurich); Ankit Singla (ETH Zurich); Wentao Wu (Microsoft Research); Ce Zhang (ETH)
  • PACE: Learning Effective Task Decomposition for Human-in-the-loop Healthcare Delivery
    Kaiping Zheng (National University of Singapore); Gang Chen (Zhejiang University); Melanie Herschel (Universität Stuttgart); Kee Yuan Ngiam (NUHS); Beng Chin Ooi (NUS)*; Jinyang Gao (Alibaba Group)
  • Automatic Optimization of Matrix Implementations for Distributed Machine Learning and Linear Algebra
    Shangyu Luo (Rice University)*; Dimitrije Jankov (Rice University); Binhang Yuan (Rice University); Chris Jermaine (Rice University)
  • Agile and Accurate CTR Prediction Model Training for Massive-Scale Online Advertising Systems
    Zhiqiang Xu (Baidu Research); Dong Li (Baidu); Weijie Zhao (Baidu Research)*; Xing Shen (Baidu); Tianbo Huang (Baidu); Xiaoyun Li (Rutgers University); Ping Li (Baidu Research)
  • ARM-Net: Adaptive Relation Modeling Network for Structured Data
    Shaofeng Cai (National University of Singapore); Kaiping Zheng (National University of Singapore); Gang Chen (Zhejiang University); H. V. Jagadish (University of Michigan); Beng Chin Ooi (NUS)*; Meihui Zhang (Beijing Institute of Technology)
  • AlphaEvolve: A Learning Framework to Discover Novel Alphas in Quantitative Investment
    Can Cui (National University of Singapore)*; Wei Wang (National University of Singapore); Meihui Zhang (Beijing Institute of Technology); Gang Chen (Zhejiang University); Zhaojing Luo (National University of Singapore); Beng Chin Ooi (NUS)
  • Tuplex: Data Science in Python at Native Code Speed
    Leonhard Spiegelberg (Brown University)*; Rahul V Yesantharao (MIT); Malte Schwarzkopf (Brown University); Tim Kraska (MIT)
  • Convergence of Array DBMS and Cellular Automata: A Road Traffic Simulation Case
    Ramon Antonio Rodriges Zalipynis (National Research University Higher School of Economics)*
  • VSS: A Storage System for Video Analytics
    Brandon Haynes (Gray Systems Lab, Microsoft)*; Maureen Daum (University of Washington); Dong He (University of Washington); Amrita Mazumdar (University of Washington); Magdalena Balazinska (UW); Alvin Cheung (University of California, Berkeley); Luis Ceze (University of Washington and OctoML)
  • An Ecosystem of Applications for Modeling Political Violence
    Aline Bessa (New York University); Vito D'Orazio (University of Texas at Dallas)*; Sonia Castelo (New York University); Mike Shoemate (Harvard University); Aécio Santos (New York University); Juliana Freire (New York University); Remi Rampin (NYU)
  • Fast Processing and Querying of 170TB of Genomics Data via a Repeated And Merged BloOm Filter (RAMBO)
    Gaurav Gupta (Rice University)*; Minghao Yan (Rice University); Benjamin Coleman (Ric); Bryce Kille (Rice University); R. A. Leo Elworth (Rice University); Tharun Medini (Rice University); Todd Treangen (Rice University); Anshumali Shrivastava (Rice University)
  • Klink: Progress-Aware Scheduling for Streaming Data Systems
    Omar Farhat (University of Waterloo)*; Khuzaima Daudjee (University of Waterloo); Leonardo Querzoni (Sapienza University of Rome)
  • To partition, or not to partition, that is the join question in a real system.
    Maximilian Bandle (TUM)*; Jana Giceva (TU Munich); Thomas Neumann (TUM)
  • Self-Tuning Query Scheduling for Analytical Workloads
    Benjamin Wagner (Technical University of Munich)*; André Kohn (Technical University of Munich); Thomas Neumann (TU Munich)
  • MxTasks: How to Make Efficient Synchronization and Prefetching Easy
    Jan Mühlig (TU Dortmund University)*; Jens Teubner (TU Dortmund University)
  • Building Advanced SQL Analytics From Low-Level Plan Operators
    André Kohn (Technical University of Munich)*; Viktor Leis ( Friedrich-Alexander-Universität Erlangen-Nürnberg); Thomas Neumann (TU Munich)
  • Jigsaw: A Data Storage and Query Processing Engine for Irregular Table Partitioning
    Donghe Kang (The Ohio State University)*; Ruochen Jiang (The Ohio State University); Spyros Blanas (The Ohio State University)
  • DFI - The Data Flow Interface for High-Speed Networks
    Lasse Thostrup (TU Darmstadt)*; Jan Skrzypczak (Zuse Institue, Berlin); Matthias Jasny (TU Darmstadt); Tobias Ziegler (TU Darmstadt); Carsten Binnig (TU Darmstadt)
  • CoRM: Compactable Remote Memory over RDMA
    Konstantin Taranov (ETH Zurich)*; Salvatore Di Girolamo (ETH Zurich); Torsten Hoefler (ETH Zürich)
  • Spitfire: A Three-Tier Buffer Manager for Volatile and Non-Volatile Memory
    Xinjing Zhou (Tencent Inc.)*; Joy Arulraj (Georgia Tech); Andrew Pavlo (Carnegie Mellon University); David E Cohen (Intel)
  • Chucky: A Succinct Cuckoo Filter for LSM-Tree
    Niv Dayan (Pliops)*; Moshe Twitto (Pliops)
  • Maximizing Persistent Memory Bandwidth Utilization for OLAP Workloads
    Björn Daase (Hasso Plattner Institute, University of Potsdam)*; Lars Jonas Bollmeier (Hasso Plattner Institute, University of Potsdam); Lawrence Benson (Hasso Plattner Institute, University of Potsdam); Tilmann Rabl (HPI, University of Potsdam)
  • Nova-LSM: A Distributed, Component-based LSM-tree Key-value Store
    Haoyu Huang (University of Southern California)*; Shahram Ghandeharizadeh (USC)
  • Efficient Uncertainty Tracking for Complex Queries with Attribute-level Bounds
    Su Feng (Illinois Institute of Technology)*; Aaron Huber (SUNY Buffalo); Oliver A Kennedy (University at Buffalo, SUNY); Boris Glavic (Illinois Institute of Technology)
  • Adaptive Compression for Fast Scans on String Columns
    Yannis E Foufoulas (University of Athens)*; Lefteris Sidirourgos (National and Kapodistrian University of Athens); Eleftherios Stamatogiannakis (University of Athens); Yannis Ioannidis (University of Athens)
  • COMPASS: Online Sketch-based Query Optimization for In-Memory Databases
    Yesdaulet Izenov (University of California, Merced); Asoke Datta (University of California, Merced); Florin Rusu (UC Merced)*; Jun Hyung Shin (University of California, Merced)
  • Vector Quotient Filters: Overcoming the Time/Space Trade-Off in Filter Design
    Prashant Pandey (LBNL & UC Berkeley)*; Alex Conway (VMware Research); Joe Durie (Rutgers University); Michael A Bender (Stony Brook); Martin Farach-Colton (Rutgers University); Rob Johnson (VMware Research)
  • Index-Accelerated Pattern Matching in Event Stores
    Michael Körber (University of Marburg)*; Nikolaus Glombiewski (University of Marburg); Bernhard Seeger (University of Marburg)
  • Efficient Approximate Algorithms for Empirical Entropy and Mutual Information
    Xingguang Chen (The Chinese University of Hong Kong); Sibo Wang (The Chinese University of Hong Kong)*
  • A-Tree: A Dynamic Data Structure to Efficiently Index Arbitrary Boolean Expressions
    Shuping Ji (Institute of Software, Chinese Academy of Sciences)*; Hans-Arno Jacobsen (University of Toronto)
  • Good to the last bit: Data-Driven Encoding with CodecDB
    Hao Jiang (University of Chicago)*; Chunwei Liu (University of Chicago); John Paparrizos (University of Chicago); Andrew A Chien (University of Chicago); Jihong Ma (Alibaba Group); Aaron J Elmore (University of Chicago)
  • Efficient String Sort with Multi-Character Encoding and Adaptive Sampling
    Wen Jin (Independent Researcher)*; Weining Qian (East China Normal University); Aoying Zhou (East China Normal University )
  • Small Selectivities Matter: Lifting the Burden of Empty Samples
    Axel Hertzschuch (Technische Universität Dresden)*; Guido Moerkotte (University of Mannheim); Wolfgang Lehner (TU Dresden); Norman May (SAP SE); Florian Wolf (SAP SE); Lars Fricke (SAP SE)
  • Conditional Cuckoo Filters
    Daniel Ting (Tableau Software)*; Rick Cole (Tableau)
  • Weighted Distinct Sampling: Cardinality Estimation for SPJ Queries
    Yuan Qiu (Hong Kong Univ. of Science and Technology ); Yilei Wang (HKUST); Ke Yi (Hong Kong Univ. of Science and Technology)*; Feifei Li (Alibaba Group); Bin Wu (Alibaba); Chaoqun Zhan (Alibaba Inc.)
  • Logical Schema Design that Quantifies Update Inefficiency and Join Efficiency
    Sebastian Link (University of Auckland)*; Ziheng Wei (University of Auckland)
  • Shedding Light on Opaque Application Queries
    Kapil Khurana (Indian Institute of Science); Jayant Haritsa (Indian Institute of Science)*
  • Worst-Case Optimal Graph Joins in Almost No Space
    Diego Arroyuelo (UTFSM, Chile); Aidan Hogan (University of Chile); Gonzalo Navarro (University of Chile); Juan Reutter (PUC)*; Javiel Rojas (University of Chile); Adrian Soto Suárez (FIC, UAI Chile)
  • Active Sampling Count Sketch (ASCS) for Online SparseEstimation of a Trillion Scale Covariance Matrix
    Zhenwei Dai (Rice University)*; Aditya Desai (Rice University); Anshumali Shrivastava (Rice University); Reinhard Heckel (Rice University)
  • One WITH RECURSIVE is Worth Many GOTOs
    Denis Hirn (Universität Tübingen); Torsten Grust (Universität Tübingen)*
  • Combining Aggregation and Sampling (Nearly) Optimally for Approximate Query Processing
    Xi Liang (University of Chicago)*; Stavros Sintos (University of Chicago); Zechao Shang (University of Chicago); Sanjay Krishnan (UChicago)
  • Resource-efficient Shared Query Execution via Exploiting Time Slackness
    Dixin Tang (University of California, Berkeley)*; Zechao Shang (University of Chicago); William W Ma (University of Chicago); Aaron J Elmore (University of Chicago); Sanjay Krishnan (U Chicago)
  • The Power of Nested Parallelism in Big Data Processing -- Hitting Three Flies with One Slap
    Gábor E. Gévay (Technische Universität Berlin)*; Jorge Arnulfo Quiane Ruiz (TU Berlin); Volker Markl (Technische Universität Berlin)
  • PGMJoins: Random Join Sampling with Graphical Models
    Ali Mohammadi Shanghooshabad (University of Warwick); Meghdad Kurmanji (University of Warwick); Qingzhi Ma (University of Warwick); Michael Shekelyan (University of Warwick); Mehrdad Almasi (University of Warwick); Peter Triantafillou (University of Warwick)*
  • TreeToaster: Towards an IVM-Optimized Compiler
    Darshana Balakrishnan (State University of New York at Buffalo)*; Carl Nuessle (University of Buffalo, SUNY); Oliver A Kennedy (University at Buffalo, SUNY); Lukasz Ziarek (University at Buffalo, SUNY)
  • HADAD: A Lightweight Approach for Optimizing Hybrid Complex Analytics Queries
    Rana Alotaibi (University of California, San Diego)*; Bogdan Cautis (University of Paris-Saclay); Alin Deutsch (UCSD); Ioana Manolescu (INRIA and Institut Polytechnique de Paris)
  • Correlation Sketches for Approximate Join-Correlation Queries
    Aécio Santos (New York University)*; Aline Bessa (New York University); Fernando Chirigati (Springer Nature); Christopher Musco (New York University); Juliana Freire (New York University)
  • Vertex-centric Parallel Computation of SQL Queries
    Ainur AS Smagulova (UC San Diego)*; Alin Deutsch (UCSD)
  • Secure Yannakakis: Join-Aggregate Queries over Private Data
    Yilei Wang (HKUST); Ke Yi (" Hong Kong University of Science and Technology, Hong Kong")*
  • PCOR: Private Contextual Outlier Releasevia Differentially Private Search
    Masoumeh Shafieinejad (University of Waterloo)*; Florian Kerschbaum (University of Waterloo); Ihab F Ilyas (U. of Waterloo)
  • Residual Sensitivity for Differentially Private Multi-Way Joins
    Wei DONG (Hong Kong University of Science and Technology, Hong Kong); Ke Yi (" Hong Kong University of Science and Technology, Hong Kong")*
  • When the Recursive Diversity Anonymity Meets the Ring Signature
    Wangze Ni (Hong Kong University of Science and Technology); Peng CHENG (East China Normal University)*; Lei Chen (Hong Kong University of Science and Technology); Xuemin Lin (University of New South Wales)
  • On Optimizing the Trade-off between Privacy and Utility in Data Provenance
    Daniel Deutch (Tel Aviv University); Ariel Frankenthal (Tel Aviv University); Amir Gilad (Duke University)*; Yuval Moskovitch (University of Michigan)
  • PRISM: Private Verifiable Set Computation over Multi-Owner Outsourced Databases
    Yin Li (Xinyang Normal University); Dhrubajyoti Ghosh (UC Irvine); Peeyush Gupta (UC Irvine); Sharad Mehrotra (U.C. Irvine); Nisha Panwar (UC Irvine); Shantanu Sharma (UC Irvine)*
  • DIV: Resolving the Dynamic Issues of Zero-knowledge Set Membership Proof in the Blockchain
    Zihuan XU (Hong Kong University of Science and Technology)*; Lei Chen (Hong Kong University of Science and Technology)
  • De-anonymization Attacks on Neuroimaging Datasets
    Vikram Ravindra (Purdue University)*; Ananth Grama (Purdue University)
  • DP-Sync: Hiding Update Patterns in Secure Outsourced Databases with Differential Privacy
    Chenghong Wang (Duke University)*; Johes Bater (Duke University); Kartik Nayak (DUKE UNIVERSITY); Ashwin Machanavajjhala (Duke)
  • MIDAS: Towards Efficient and Effective Maintenance of Canned Patterns in Visual Graph Query Interfaces
    Kai Huang (Fudan University); Huey Eng CHUA (Nanyang Technological University); Sourav S Bhowmick (Nanyang Technological University)*; Byron Choi (Hong Kong Baptist University); Shuigeng Zhou (Fudan University)
  • Exploring Ratings in Subjective Databases
    Sihem Amer-Yahia (CNRS); Tova Milo (Tel Aviv University); Brit Youngmann (Tel Aviv University)*
  • Synthesizing Natural Language to Visualization (NL2VIS) Benchmarks from NL2SQL Benchmarks
    Yuyu Luo (Tsinghua University); Nan Tang (Qatar Computing Research Institute, HBKU); Guoliang Li (Tsinghua University)*; Chengliang Chai (Tsinghua University); Wenbo Li (清华大学); Xuedi Qin (Tsinghua University)
  • MetaInsight: Automatic Discovery of Structured Knowledge for Exploratory Data Analysis
    Pingchuan Ma (HKUST)*; Rui Ding (Microsoft Research); Shi Han (Microsoft Research); Dongmei Zhang (Microsoft Research Asia)
  • DataPrep.EDA: Task-Centric Exploratory Data Analysis for Statistical Modeling in Python
    Jinglin Peng (Simon Fraser University); Weiyuan Wu (Simon Fraser University)*; Brandon Lockhart (Simon Fraser University); Song Bian (The Chinese University of Hong Kong); Jing Nathan Yan (Cornell University); Linghao Xu (Simon Fraser University); Zhixuan Chi (Simon Fraser University); Jeffrey M Rzeszotarski (Cornell University); Jiannan Wang (Simon Fraser University)
  • Interactive Search for One of the Top-k
    Weicheng Wang (Hong Kong University of Science and Technology)*; Raymond Chi-Wing Wong (Hong Kong University of Science and Technology); Min Xie (Shenzhen Institute of Computing Sciences )
  • To Share, or not to Share Online Event Trend Aggregation Over Bursty Event Streams
    Olga Poppe (Microsoft)*; Chuan Lei (IBM Research - Almaden); Lei Ma (WPI); Allison M Rozet (MathWorks); Elke A Rundensteiner (WPI)
  • Distributed Stream kNN Join
    Seyedamirhesam Shahvarani (Technical University of Munich)*; Hans-Arno Jacobsen (TUM)
  • EIRES: Efficient Integration of Remote Data in Event Stream Processing
    Bo Zhao (Humboldt University of Berlin)*; Han van der Aa (Universität Mannheim); Thanh Tam Nguyen (Leibniz Universitat Hannover); Quoc Viet Hung Nguyen (Griffith University); Matthias Weidlich (Humboldt-Universität zu Berlin)
  • MuSE Graphs for Flexible Distribution of Event Stream Processing in Networks
    Samira Akili (HU Berlin )*; Matthias Weidlich (Humboldt-Universität zu Berlin)
  • Incrementalizing Graph Algorithms
    Wenfei Fan (Univ. of Edinburgh ); Chao Tian (Alibaba Group)*; Ruiqi Xu (University of Edinburgh); Qiang Yin (Alibaba Group); Wenyuan Yu (Alibaba Group); Jingren Zhou (Alibaba Group)
  • Making Graphs Compact by Lossless Contraction
    Wenfei Fan (Univ. of Edinburgh ); Yuanhao Li (University of Edinburgh)*; Muyang Liu (University of Edinburgh); Can Lu (SICS)
  • GPU-Accelerated Graph Label Propagation for Real-Time Fraud Detection
    chang ye (Singapore Management University)*; Yuchen Li (Singapore Management University); Bingsheng He (National University of Singapore); Zhao Li (Alibaba Group); Jianling Sun (Zhejiang University)
  • HUGE: An Efficient and Scalable Subgraph Enumeration System
    Zhengyi Yang (University of New South Wales)*; Longbin Lai (Alibaba Corporation); Xuemin Lin (University of New South Wales); Kongzhang Hao (University of New South Wales); Wenjie Zhang (University of New South Wales)
  • Dynamic Structural Clustering on Graphs
    Boyu Ruan (University of Queensland); Junhao Gan (University of Melbourne)*; Hao Wu (University of Melbourne); Anthony Wirth (The University of Melbourne)
  • To Intervene or Not To Intervene: Cost based Intervention for Combating Fake News
    Saravanan Thirumuruganathan (QCRI)*; Michael Simpson (University of British Columbia); Laks V.S. Lakshmanan (The University of British Columbia)
  • iTurboGraph: Scaling and Automating Incremental Graph Analytics
    Seongyun Ko (POSTECH)*; Taesung Lee (POSTECH); Kijae Hong (POSTECH); Wonseok Lee (POSTECH); In Seo (POSTECH); Jiwon Seo (Hanyang University); Wook-Shin Han (POSTECH)
  • Cache-Efficient Fork-Processing Patterns on Large Graphs
    Shengliang Lu (National University of Singapore)*; Shixuan Sun (National University of Singapore); Johns Paul (NUS); Yuchen Li (Singapore Management University); Bingsheng He (National University of Singapore)
  • LightNE: A Lightweight Graph Processing System for Network Embedding
    Jiezhong Qiu (Tsinghua University)*; Laxman Dhulipala (MIT CSAIL); Jie Tang (Tsinghua University); Richard Peng (Georgia Tech / MSR Redmond); Chi Wang (Microsoft Research)
  • RisGraph: A Real-Time Streaming System for Evolving Graphs to Support Sub-millisecond Per-update Analysis at Millions ops/s
    Guanyu Feng (Tsinghua University)*; Zixuan Ma (Tsinghua University); Daixuan Li (Tsinghua University); Shengqi Chen (Tsinghua University); Xiaowei Zhu (Tsinghua University); Wentao Han (Tsinghua University); Wenguang Chen (Tsinghua University)
  • Efficient Graph Summarization using Weighted LSH at Billion-Scale
    Quinton Yong (University of Vcitoria); Mahdi Hajiabadi (University of Victoria)*; Venkatesh Srinivasan (university of victoria); Alex Thomo (University of Victoria)
  • A Learned Sketch for Subgraph Counting
    Kangfei Zhao (The Chinese University of Hong Kong)*; Jeffrey Xu Yu (Chinese University of Hong Kong); Hao Zhang (Chinese University of Hong Kong); Qiyan Li (Wuhan University ); Yu Rong (Tencent AI Lab)
  • Hybrid Edge Partitioner: Partitioning Large Power-Law Graphs under Memory Constraints
    Ruben Mayer (Technical University of Munich)*; Hans-Arno Jacobsen (TUM)
  • Efficient Exploration of Interesting Aggregates in RDF Graphs
    Yanlei Diao (Ecole Polytechnique); Pawel Guzewicz (Inria)*; Ioana Manolescu (INRIA and Institut Polytechnique de Paris); Mirjana Mazuran (INRIA Saclay)
  • Terrace: A Hierarchical Graph Container for Skewed Dynamic Graphs
    Prashant Pandey (LBNL & UC Berkeley)*; Brian Wheatman (Johns Hopkins University); Helen Xu (MIT); Aydin Buluc (Lawrence Berkeley National Laboratory)
  • Compliant Geo-distributed Query Processing
    Kaustubh Beedkar (TU Berlin)*; Jorge Arnulfo Quiane Ruiz (TU Berlin); Volker Markl (Technische Universität Berlin)
  • Don't Look Back, Look into the Future: Prescient Data Partitioning and Migration for Deterministic Database Systems
    Yu-Shan Lin (National Tsing Hua University); Ching Tsai (National Tsing Hua University); Tz Yu Lin (National Tsing Hua University); Yun-Sheng Chang (National Tsing Hua University); Shan-Hung Wu (National Tsing Hua University)*
  • PigPaxos: Devouring the Communication Bottlenecks in Distributed Consensus
    Aleksey Charapko (University of New Hampshire); Ailidani Ailijiang (Microsoft); Murat Demirbas (University at Buffalo, SUNY)*
  • Asynchronous Prefix Recoverability for Fast Distributed Stores
    Tianyu Li (Massachusetts Institute of Technology)*; Badrish Chandramouli (Microsoft Research); Jose Faleiro (Microsoft); Samuel Madden (MIT); Donald Kossmann (Microsoft Research)
  • MG-Join: A Scalable Join for Massively Parallel Multi-GPU Architectures
    Johns Paul (Nanyang Technological University)*; Bingsheng He (National University of Singapore); Shengliang Lu (National University of Singapore); Chiew Tong Lau (Nanyang Technological University)
  • Instance-Optimized Data Layouts for Cloud Analytics Workloads
    Jialin Ding (MIT)*; Umar Farooq Minhas (Microsoft Research); Badrish Chandramouli (Microsoft Research); Chi Wang (Microsoft Research); Yinan Li (Microsoft Research); Ying Li (Microsoft); Donald Kossmann (Microsoft Research); Johannes Gehrke (Microsoft); Tim Kraska (MIT)
  • Fast Density-Peaks Clustering: Multicore-based Parallelization Approach
    Daichi Amagata (Osaka University)*; Takahiro Hara (Osaka University, Japan)
  • Fast and Exact Outlier Detection in Metric Spaces: A Proximity Graph-based Approach
    Daichi Amagata (Osaka University)*; Makoto Onizuka (Osaka University); Takahiro Hara (Osaka University, Japan)
  • Top-K Deep Video Analytics: A Probabilistic Approach
    Ziliang Lai (Chinese University of Hong Kong)*; Chenxia Han (Chinese University of Hong Kong); Chris Liu (Chinese University of Hong Kong); Pengfei Zhang (Chinese University of Hong Kong); Eric Lo (Chinese University of Hong Kong); Ben Kao (University of Hong Kong)
  • At-the-time and Back-in-time Persistent Sketches
    Benwei Shi (University of Utah)*; Zhuoyue Zhao (University of Utah); Yanqing Peng (University of Utah); Feifei Li (University of Utah); Jeff Phillips (University of Utah)
  • Evaluating Temporal Queries Over Video Feeds
    Yueting Chen (York University )*; Xiaohui Yu (York University); Nick Koudas (University of Toronto); Ziqiang Yu (Yantai University)
  • Consistent and Flexible Selectivity Estimation for High-Dimensional Data
    Yaoshu Wang (Shenzhen Institute of Computing Sciences, Shenzhen University); Chuan Xiao (Osaka University); Jianbin Qin (Shenzhen Institute of Computing Sciences, Shenzhen University)*; Rui Mao (Shenzhen Institute of Computing Sciences, Shenzhen University); Makoto Onizuka (Osaka University); Wei Wang (University of New South wales); Rui Zhang (" University of Melbourne, Australia"); Yoshiharu Ishikawa (Nagoya University)
  • Spatial Independent Range Sampling
    Dong Xie (University of Utah)*; Jeff Phillips (University of Utah); Michael Matheny (Amazon); Feifei Li (University of Utah)
  • On m-Impact Regions and Standing Top-k Influence Problems
    Bo Tang (Southern University of Science and Technology); Kyriakos Mouratidis (Singapore Management University)*; Mingji Han (Southern University of Science and Technology)
  • RobustPeriod: Robust Time-Frequency Mining for Multiple Periodicity Detection
    Qingsong Wen (Alibaba DAMO Academy)*; Kai He (Alibaba DAMO Academy); Liang Sun (Alibaba Group); Yingying Zhang (Alibaba Group); Min Ke (Alibaba Group); Huan Xu (Alibaba Group)
  • Point-to-Hyperplane Nearest Neighbor Search Beyond the Unit Hypersphere
    Qiang Huang (National University of Singapore)*; Yifan Lei (National University of Singapore); Anthony Tung (NUS)
  • Public Transport Planning: When Transit Network Connectivity Meets Commuting Demand
    Sheng Wang (New York University)*; Yuan Sun (Monash University); Christopher Musco (New York University); Zhifeng Bao (RMIT University)
  • P2H: Efficient Distance Querying on Road Networks by Projected Vertex Separators
    Zitong Chen (Chinese University of Hong Kong)*; Ada Wai-Chee Fu (Chinese University of Hong Kong); Minhao Jiang (TuSimple); Eric Lo (Chinese University of Hong Kong); Pengfei Zhang (Chinese University of Hong Kong)
  • PathEnum: Towards Real-Time Hop-Constrained s-t Path Enumeration
    Shixuan Sun (National University of Singapore)*; Yuhang Chen (National University of Singapore); Bingsheng He (National University of Singapore); Bryan Hooi (NUS)
  • Efficiently Answering Durability Prediction Queries
    Junyang Gao (Duke University)*; Yifan Xu (Amazon.com); Pankaj K Agarwal (Duke University); Jun Yang (Duke University)

Credits
Follow our progress: FacebookTwitter