Research

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Our research interests revolve around theoretical modeling and experimental understanding of multi-instrument measurement systems that deal with multi-dimensional multi-variate data, as well as, around automation of common image pre-processing and analysis tasks. Based on our past work, our research could also be described as X-informatics, where the X stands for bio, hydro, medical image, or sensor.

Research Statement

Our research involves research and development of solutions to real life problems, often in collaboration with other scientists (in our terminology "domain" scientists) in the application areas of machine vision, synthetic aperture radar (SAR) target and scene modeling, land use and land cover classification, bio-informatics, microscopy and medical image processing, geo-spatial information systems (GIS) and advanced sensor environments. The work draws from theoretical foundations of image and video processing, computer vision, statistical modeling, data mining and pattern recognition, software engineering and sensor design.

The main goal of our research and development is to automate information processing of repetitive, laborious and tedious analysis tasks and build user-friendly decision-making systems that operate in automated or semi-automated mode.

Peter Bajcsy

Dr. Peter Bajcsy has left NCSA in June 2011 for a position at NIST.

  • ISDA Group leader and Research Scientist, NCSA
  • Adjunct Professor of Electrical and Computer Engineering and Computer Science Departments
  • Associate Director for Data Analytics and Pattern Recognition, Institute for Computing in Humanities, Arts and Social Science (I-CHASS)
  • Illinois Informatics Institute (I3)

Web-based Services

Research and Development Themes; Current projects
  1. CyberInfrastructure environments: Workflow environments, provenance information gathering.
  2. Analyses of Electronic Records and Historical Documents: Image/text/vector graphics extraction from PDF documents, storage and information retrieval tradeoffs, loss introduced by file format conversions, integrity verifications, grouping of electronic records, optical character recognition from paper forms, automated detection of regions of interest in image scans, information aggregation and classification, and knowledge repository building from extracted information.

    Understanding Preservation and Reconstruction of Electronic Records:

    Historical Documents:

  3. Intelligent spaces: Hazard sensing: Wireless sensor communication; Spectral sensor registration and calibration; Multi-sensor data fusion; Collaborative robot control for sensor deployment; Spatially adaptive hazard sensing;

    Tele-immersive Environments:

  4. Multi-spectral and hyper-spectral analysis and modeling: Raster and vector data processing; Feature extraction and selection from high-dimensional data; Statistical, model-based and hybrid scene analysis and synthesis.
  5. Medical and bioinformatics data: 3D reconstruction from 2D confocal microscopy imagery; Microarray data analysis; Data integration of 3D multi-modal data: MRI, DTI, histology;
  6. Data mining of large size datasets with geospatial information: Integration of remote sensing, airborne imagery and ground measurements.
    Geospatial information systems: Integration of raster, vector and tabular data with georeferencing information, uncertainty analysis of integration;

    Large Datasets with Geospatial Information:

All (current and past) projects


Software Libraries

Main page
  Image To Learn (Im2Learn)
  CyberIntegrator
  Spatial Pattern To Learn (SP2Learn)
  Image Provenance To Learn (IP2Learn)
  Geospatial Image To Learn (GeoLearn)
  Polyglot
  Document To Learn
  File To Learn