Scholar
Xiao Hu
Google Scholar ID: rTXGtQ8AAAAJ
University of Waterloo
Citations & Impact
Citations
491
H-index
12
i10-index
15
Publications
20
Co-authors
26
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Published multiple papers in top conferences such as PODS and SIGMOD, including:
- - "Output-Optimal Algorithms for Join-Aggregate Queries" (PODS 2025, Best Paper Award)
- - "Fast Matrix Multiplication meets the Submodular Width" (PODS 2025, Distinguished Paper Award)
- - "Towards Update-Dependent Analysis of Query Maintenance" (PODS 2025)
- - "Smallest Synthetic Witnesses for Conjunctive Queries" (PODS 2025)
- - "Computing A Well-Representative Summary of Conjunctive Query Results" (PODS 2025)
- - "Oblivious Optimal Algorithms for Multi-way Joins" (ICDT 2025)
- - "Reservoir Sampling over Joins" (SIGMOD Record 2025, invited)
- - "Fast Matrix Multiplication for Query Processing" (PODS 2024)
- - "Topology-aware Parallel Joins" (PODS 2024, Distinguished Paper Award)
- - "Reporting Durable Patterns in Temporal Graphs Efficiently" (PODS 2024)
- - "Reservoir Sampling over Joins" (SIGMOD 2024, Best Paper Award Honorable Mention, SIGMOD Research Highlight Award)
- - "NOCAP: Near-Optimal Correlation-Aware Partitioning Joins" (SIGMOD 2024)
- - "Finding Smallest Witness for Conjunctive Query" (ICDT 2024, Best Paper Award)
Research Experience
- Currently an Assistant Professor at the Cheriton School of Computer Science, University of Waterloo. Research areas involve new algorithms and complexity results for database query processing, as well as how these algorithms can be applied to high-dimensional, unstructured, and multimodal data.
Background
- Research interests include efficient query engines, new algorithms and complexity results for database query processing. The goal is to make next-generation data systems run faster, use fewer resources, and adapt optimally to new constraints. Also focuses on algorithms for high-dimensional, unstructured, and multimodal domains.
Miscellany
- Looking for highly motivated Ph.D. and MMath students to join his team, focusing on both theoretical foundations and emerging areas.
