Jianting Zhang's Picture

Jianting Zhang

Associate Professor in Geographical Information System (GIS) and Computer Science

CS@CUNY City College (Primary)


Geospatial Technologies and Environmental Cyberinfrastructure (GeoTECI) Lab

NSF IIS-Medium Collaborative: Spaital Data and Trajectory Data Managment on GPUs

Facutly Profile[Education/Training] [Professional Experiences] [Courses] [Contact Info]

GeoTECI Lab [Overview (9 slides)] [Students] [Archieved News]

Recent News:
[08/20/2014] A brief introduction to my research and my group (GeoTECI lab) with 9 slides is added.
[12/10/2014] I was a recipient of the CUNY Certificate of Recognition for the year 2014.  
[03/11/2015] GeoTECI Ph.D. Student Simin You has released his SpatialSpark source code at GitHub [Link]. The related CloudDM'15 paper can be found here.
[04/02/2015] A summary of our work on GPU-based geospatial processing over the past five years (2009-2014) entitled "Large-Scale Spatial Data Processing on GPUs and GPU-Accelerated Clusters" appeared at the ACM SIGSPATIAL Special as an invited paper. Click here for a local copy. 
[07/03/2015] We have released the source code of our ISP prototypes (including ISP-MC, ISP-MC+ and ISP-GPU). Click here for the code and here for the HardBD'15 paper as a high level documentation. It has been a very tough yet pleasant journey to learn advanced features of Impala and integrate our single node data parallel spatial indexing and spatial join techniques (on GPUs as well as multi-core CPUs) into Cloudera  Impala. The learnt experiences and lessons lead us to the design and implementation of LDE as a succession to ISP.

[12/29/2015] GeoTECI Ph.D. Student Simin You has sucessfully defended his dissertation on 11/30 and completed all the procedures for graduation recently. The PDF file of Dr. You's disseration, entiled "Large-scale spatial data management on modern parallel and distributed platforms", can be downloaded here (139 pages). Congratulations!
[09/01/2016] Zuliang Zhao, a Ph.D. student from Chinese Agricultural University (CAU) joined GeoTECI Lab as a visiting student for two years. His visit is funded by China Scholarship Council (CSC).
[10/30/2016] Our paper, entitled "
High-performance polyline intersection based spatial join on GPU-accelerated clusters", was accepted by ACM BigSpatial'16 workshop. Click here for a copy at ACM Digital Library. 

Research Interests

·        High-Performance Geospatial Computing (HPC-G)

·        Spatial Databases (SDB) and GIS Applications (GIS)

·        Environmental Cyberinfrastructure (CI)

·        Geospatial Visual Analytics (GVA)

·        Multispectral and Hyperspectral Remote Sensing Data Processing (RS)

Publication (DBLP)

        ·  By Year: 2016 2015 2014, 2013, 2012, 2011, 2010 2009, 2008, 2007, 2006, 2005, 2004, 2003, 2002, 2001, 2000, 1999, 1998, 1997


Research Initiatives and Exploratory Projects [Funded Projects] (* source code available)

·   High-Performance Geospatial Computing on GPGPUs [HPC-G (Position Paper-2010)]
(1) Non-Query Spatial Operations: [NNI-DEM][Polygon Rasterization]

                        (2) Spatial Indexing: [BMMQ-Tree*] [BQ-Tree*][Point-Quadtree*][R-Tree*] [MA-Quadtree for Indexing Polygon Internals]

                        (3) End-to-End Systems for Spatial Joins (10-40X over in-memory systems and 3-4 orders of speedups over disk-resident systems)
                             [Point to Netwfork][Point in Polygon][Point to Polygon][Trajectory to Trajectory]
                        (4) From Single-Node to Distributed Clusters: [SpatialSpark*][ISP* (MC, MC+, GPU)] [LDE]

                        (5) In-Progress (Algorithms): [Selectivity Estimation] [Polygon to Polygon Join (Overlay)]
                        (6) In-Progress (Systems) [Spatial SQL Front-end] [Hybrid CPU-GPU Systems]

·     Managing Large-Scale  OD/Trajectory Data with Applications to Data Mining of Traffic and Travel Patterns
[U2SOD-DB] [U2SOD-VA][NYC Case Studies] [Frequenet Sequence Mining using Shortcuts]

·     Managing Large-Scale Environmental and Species Distribution Data with Applications to Understanding Global and Regional Biodiversity Patterns  [Visual Explorations of Rasters] [USGS Little Tree Range Map] [NatureServe Bird Range Map in DBMSs] [Lightweight Compression for Rasters*] [Zonal Summation of GBIF Data on GPUs]