Jianting Zhang's Picture

Jianting Zhang

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


Affilications:
CS@CUNY City College (Primary)

CS@CUNY Graduate CenterNOAA-CRESTUTRC,
CCSI@ORNL (through DOE VFP)


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][Archieved News]

GeoTECI Lab [Overview (9 slides)] [Students] [Hardware] [Software][Data] [Research Code and Online Demos]

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. 
[05/12/2015] The GeoTECI lab received an unrestricted gift fund from Pitney Bowes Inc.,the parent company of MapInfo GIS,  to build collaboration on processing large-scale geospatial data in parallel and distributed computing environments.
[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 Impala. The learnt experiences and lessons lead us to the design and implement of LDE as a succession to ISP.
[07/08/2015] I am one of the faculty to win Silicon Mechanics' fourth annual Research Cluster Grant led by Prof. David Jeruzalmi (Chemistry and Biochemistry). The press release from CCNY is here. The specification of the cluster is here. The cluster, while small in scale, represents the most advanced architecture of most recent clusters (including GPU and Infiniband).
[07/10/2015] CUNY Board of Trustees approved my tenure and promption recommeded by City College on 06/29. I am now an Associate Professor at the City College of New York (CUNY City College). I will be on sabbatical leave from CCNY 09/15-05/16.

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 Topics (Selected): HPC-G, SDB, GIS, RS, GVA, CI

        ·        By Year: 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]

·   High-Performance Geospatial Computing on GPGPUs [Overview] (* Experimental Source Code)
(1) Previous Results: [HPC-G (Position Paper)] [BMMQ-Tree] [BQ-Tree] [NNI-DEM][Polygon Rasterization]

                        (2) Reference Primitives based Implementations [PrimQuad*][PrimCSPTP*][PrimTrQuery*] [PrimSpJoin*]
                        (3) Spatial Indexing and Query Optimization: [R-Tree][Selectivity Estimation]

                        (4) 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 Network][Point in Polygon][Point to Polygon][Trajectory to Trajectory]

                        (5) In-Progress (Algorithms): [Indexing Polygon Internals] [Increamental Refining Filtering]  [Polygon to Polygon Join (Overlay)]
                        (6) In-Progress (Systems) [LLVM-based Spatial SQL Front-end] [Hybrid CPU-GPU Systems] [Scaling-Out to Clusters]

·     Managing Large-Scale  OD/Trajectory Data with Applications to Data Mining of Traffic and Travel Patterns [Overview]
[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  [Overview] [Visual Exploreations of Rasters] [Lightweight Compression for Rasters] [USGS Little Tree Range Map] [NatureServe Bird Range Map in DBMSs] [Zonal Summation of GBIF Data on GPUs]

·    Web-based Query-Driven Visual Exploration of Large-Scale Geospatial Data (*Online Accessible)
 
[Overview] [NYC CrashMap*][BirdsQuests*][RasterExplorer*] [HP-GVE]