Jia Yu

Assistant Professor

Washington State University

Biography

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 Geoinformatica 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 me in Spring 2021. Please read this page.

Call For Papers and Call For Participation

WSU will host 2020 Digital Agriculture Summit (online) on October 6-7. Researchers, industry, and government policy makers are invited to provide their insights. Register Today!
1st ACM SIGSPATIAL International Workshop on Modeling and Understanding the Spread of COVID-19

News

09/21/2020: A journal paper about scalable geospatial data visualization has been accepted to VLDB Journal
09/15/2020: Apache Sedona (incubating) codebase has been migrated to github.com/apache/incubator-sedona and the new website sedona.apache.org is online.
08/16/2020: I officially joined Washington State University School of Electrical Engineering and Computer Science as a tenure-track assistant professor!
07/19/2020: Our open-source big geospatial data computing engine, Apache Sedona (formerly GeoSpark), has been accepted to The Apache Software Foundation (the home of Hadoop, Spark, Flink, and many more) and now is under incubation. New website, Git repo, and other infra will be online soon. Thanks for the support from everyone in this process!
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.
05/18/2020: Successfully defended my dissertation!
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)

Experience

Assistant Professor

Washington State University, School of Electrical Engineering and Computer Science

Aug 2020 – Present Pullman, Washington

Research Intern

Microsoft Research, Database group

Jun 2019 – Aug 2019 Redmond, Washington

– Microsoft is the birthplace of Micrsoft SQL Server
– Mentor / Collaborators: Umar Farooq Minhas, David Lomet, Jaeyoung Do, Yinan Li, Chi Wang, Badrish Chandramouli, Johannes Gehrke, Donald Kossmann
– I worked on a realistic design of updatable learned indices
– SIGMOD 2020 research paper ALEX: An Updatable Adaptive Learned Index

Research Intern

IBM Almaden Research Center, Database group

May 2018 – Aug 2018 San Jose, California

– IBM-Almaden is the birthplace of relational model, SQL and DB2 DBMS
– Mentor / Collaborators: Vijayshankar Raman, Yingjun Wu, Yuanyuan Tian, Ronald Barber, Richard Sidle
– I participated in Hermit project to design a succinct secondary index. I also explored the code generation issues on compressed database tables and implemented a preliminary code generator with JIT execution using LLVM, for IBM HTAP system
– SIGMOD 2019 research paper Designing Succinct Secondary Indexing Mechanism by Exploiting Column Correlations
– VLDB 2019 demo paper HERMIT in action: Succinct secondary indexing mechanism via correlation exploration

Software Development Intern

Apple, Maps team

Aug 2016 – Jun 2016 Cupertino, California

– Apple is the birthplace of Apple Maps
– Mentor: Huang-Hsiang Cheng; Manager: Alex Radeski
– I deployed and improved distributed computing frameworks and resource management systems such as Apache Spark and Apache Mesos. I also developed internal evaluation tools to assist large-scale geospatial analysis

Projects

ALEX

ALEX is a new class of learned indexes which addresses issues that arise when implementing dynamic and updatable learned indexes.

PDF Code

Tabula

Tabula is a middleware that runs on top of a SQL data system with the purpose of increasing the interactivity of geospatial visualization dashboards.

PDF Code Video

GeoSparkSim

GeoSparkSim is a scalable traffic simulator which extends Apache Spark to generate large-scale road network traffic datasets with microscopic traffic simulation.

PDF Code Slides Video Follow

Hermit

Hermit is a succinct secondary indexing mechanism for modern RDBMSs. It judiciously leverages the rich soft functional dependencies hidden among columns to prune out redundant structures for indexed key access.

PDF Video

GeoSparkViz

GeoSparkViz is a large-scale geospatial map visualization framework. GeoSparkViz extends Apache Spark to provide native support for general cartographic design.

PDF Code Follow

Hippo

Hippo is a fast, yet scalable, database indexing approach. It significantly shrinks the index storage and mitigates maintenance overhead without compromising much on the query execution performance.

PDF Code Slides Video

GeoSpark

GeoSpark is a cluster computing system for processing large-scale spatial data. GeoSpark extends Apache Spark / SparkSQL to efficiently load, process, and analyze large-scale spatial data across machines.

PDF Code Slides Follow

Selected Publications

Jia Yu, Mohamed Sarwat (2020). GeoSparkViz: A Cluster Computing System for Visualizing Massive-Scale Geospatial Data. In VLDB Journal.

Code Project Project website

Jialin Ding, Umar Farooq Minhas, Jia Yu, Chi Wang, Hantian Zhang, Yinan Li, Jaeyoung Do, Donald Kossmann, Johannes Gehrke, David Lomet, Badrish Chandramouli, Tim Kraska (2020). ALEX: An Updatable Adaptive Learned Index. In ACM SIGMOD.

PDF Code Project Technical report

Jia Yu, Mohamed Sarwat (2020). Turbocharging Geospatial Visualization Dashboards via a Materialized Sampling Cube Approach. In IEEE ICDE.

PDF Code Project

Yingjun Wu, Jia Yu, Yuanyuan Tian, Ronald Barber, Richard Sidle (2019). Designing Succinct Secondary Indexing Mechanism by Exploiting Column Correlations. In ACM SIGMOD.

PDF Project

Jia Yu, Zongsi Zhang, Mohamed Sarwat (2019). Spatial Data Management in Apache Spark: the GeoSpark Perspective and Beyond. In Geoinformatica.

PDF Code Project Project website

Jia Yu, Mohamed Sarwat (2016). Two Birds, One Stone: A Fast, yet Lightweight, Indexing Scheme for Modern Database Systems. In VLDB.

PDF Code Project

Recent publications

Quickly discover relevant content by filtering publications.

Jia Yu, Mohamed Sarwat (2020). GeoSparkViz: A Cluster Computing System for Visualizing Massive-Scale Geospatial Data. In VLDB Journal.

Code Project Project website

Jia Yu, Kanchan Chowdhury, Mohamed Sarwat (2020). Tabula in Action: A Sampling Middleware for Interactive Geospatial Visualization Dashboards. In VLDB.

Code Project

Jia Yu, Zishan Fu, Mohamed Sarwat (2020). Dissecting GeoSparkSim: A Scalable Microscopic Road Network Traffic Simulator in Apache Spark. In Distributed and Parallel Databases, DAPD.

Code Project Project website

Jialin Ding, Umar Farooq Minhas, Jia Yu, Chi Wang, Hantian Zhang, Yinan Li, Jaeyoung Do, Donald Kossmann, Johannes Gehrke, David Lomet, Badrish Chandramouli, Tim Kraska (2020). ALEX: An Updatable Adaptive Learned Index. In ACM SIGMOD.

PDF Code Project Technical report

Jia Yu, Mohamed Sarwat (2020). Turbocharging Geospatial Visualization Dashboards via a Materialized Sampling Cube Approach. In IEEE ICDE.

PDF Code Project

See all publications

Awards

Best Demo Paper Runner-Up

International Symposium on Spatial and Temporal Databases, SSTD Aug 2019

Engineering Graduate Fellowship

Arizona State University, Ira A. Fulton Schools of Engineering Apr 2019

Third Place of Student Research Competition

ACM SIGSPATIAL Nov 2017

Student Travel Grant

National Science Foundation, Microsoft Jan 2015 – Jan 2020

IEEE ICDE (3 times), ACM SIGSPATIAL (5 times = 4 NSF + 1 Microsoft)

Outstanding graduate

Northwest Agriculture and Forestry University Jul 2013

Only 200 out of 5600 students were selected

First-class Scholarship, Merit Student

Northwest Agriculture and Forestry University Sep 2011 – Sep 2012

2 times, only top 10% students (in terms of GPA) were selected

Services

Program Committee member

International conferences 2020 – 2020

ACM SIGSPATIAL 2020

Invited reviewer

International journals 2018 – 2020

VLDB Journal (VLDBJ)
ACM Transactions on Spatial Algorithms and Systems (TSAS)
International Journal of Geographical Information Science (IJGIS)
Geoinformatica Journal
IEEE Transactions on Cloud Computing (TCC)
Computers and Geosciences (CAGEOS)
IEEE Transactions on Parallel and Distributed Systems (TPDS)
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Frontiers in Big Data

See certificate

External reviewer

International conferences 2016 – 2020

SIGMOD: 2017, 2018, 2019
SIGMOD demo: 2016, 2018
PVLDB: 2016, 2017, 2018, 2019, 2020
ICDE: 2020
ICDE demo: 2017, 2018
SIGSPATIAL: 2016, 2017, 2018
SSTD: 2017
MDM: 2016