Jia Yu is an Assistant Professor at Washington State University School of Electrical Engineering and Computer Science. He obtained his Ph.D. in Computer Science from Arizona State University (advisor: Mohamed Sarwat) in Summer 2020. His research focuses on large-scale database systems and geospatial data management. In particular, he worked on distributed geospatial data management systems, database indexing, and geospatial data visualization. Jia’s research outcomes have appeared in the most prestigious database / GIS conferences and journals, including SIGMOD, VLDB, ICDE, SSTD and VLDB Journal. He is the main contributor of several open-sourced research projects such as Apache Sedona (incubating), a cluster computing framework for processing big spatial data, which receives 200,000 downloads per month and has users / contributors from major companies (e.g., Facebook, Uber, AT&T, and MoBike).

Here is a one-page summary of my research.

I am actively looking for Computer Science PhD students to join my lab. Financial support is available. Please read this page.

News

  • Welcome a new PhD student to my lab: Congying Wang. She obtained her bachelor and master in Computer Science from University at Buffalo.
  • 12/13/2020: Invited to be a Program Committee member of VLDB (Very Large Data Bases) 2021 Demo Track.
  • 11/30/2020: Invited to be a Program Committee member of SSTD (Symposium on Spatial and Temporal Databases) 2021.
  • 09/21/2020: A journal paper about scalable geospatial data visualization has been accepted to VLDB Journal
  • 09/15/2020: Our open-source big geospatial data computing engine, Apache Sedona (incubating, formerly GeoSpark), has been accepted to The Apache Software Foundation. GitHub, Website: sedona.apache.org
  • 07/06/2020: Our ALEX index, an updatable adaptive learned index, is now open-source on GitHub: Microsoft ALEX. Our implementation is a near drop-in replacement for std::map or std::multimap.
  • 06/29/2020: A journal paper about scalable traffic simulation has been accepted to Distributed and Parallel Databases Journal.
  • 06/04/2020: A demo paper about Tabula sampling middleware has been accepted to PVLDB 2020.
  • 05/22/2020: Invited to be a Program Committee member of SIGSPATIAL 2020.
  • 03/13/2020: A research paper about “Updatable Adaptive Learned Index” has been accepted to SIGMOD 2020. [ 16-page version, 21-page MSR technical report] This is part of my Summer 2019 intern work with Microsoft Research and MIT.

Interests

  • Database systems
  • Distributed data systems
  • Geospatial data management

Education

  • Ph.D. in Computer Science, 2020

    Arizona State University

  • BEng in Software Engineering, Outstanding Graduate, 2013

    Northwest Agriculture and Forestry University, China (西北农林科技大学)

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