Faculty

Institution

Unit

Venue

John C Hart

Professor

University of Illinois Urbana-Champaign

Affiliations

The Grainger College of Engineering

Siebel School of Computing and Data Science

John C Hart is currently serving as a Siebel School Of Computing And Data Science Professor at University of Illinois Urbana-Champaign.

Honors

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Experiences

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Education

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John C Hart

University of Illinois Urbana-Champaign

Professor

You can click a keyword to filter the displayed items

computer graphics computer science graphics geometric modeling computational geometry digital image processing visualization applied mathematics image analysis computer-aided design computational imaging computer vision computer engineering machine vision geometry scientific computing image representation information visualization geometry processing real-time computer graphics surface modeling mathematics realistic rendering computer graphic technique interactive computer graphics fractals fractal analysis visual computing graphic interface shape modeling multimedia computing automated inspection parallel programming texture (visual arts) shape analysis object detection geometric topology high performance computer architecture mesh reduction mesh optimization gpu computing volume rendering illumination modeling computational illumination image segmentation multimedia systems computational topology geometry generation geometry compression network visualizations graph analysis procedural generation ray tracing numerical algorithms cluster computing edge detection non-photorealistic rendering graph drawing procedural modeling texture atlas linear fractals visual inspection implicit surface riprap rock subdivision surfaces unstructured mesh generation procedural approach geometry image shading hardware real-time procedural shading real-time shading deep learning techniques particle system data structure ballast scanning vehicle ballast degradation interactive visualization data and information visualization data science computational visualization

Notable Scholarly Works

Notable Federal Grants

Collaborators

I-Ballast: Computer Vision Solutions for Ballast Degradation Analysis Using Deep-Learning and Data Fusion Methods. Geodata and AI. (2025)

Kelin DingJiayi LuoHaohang HuangJohn M. HartIssam I.A. QamhiaErol TutumluerHugh ThompsonTheodore R. Sussmann

data fusion methodsdeblurringengineeringmulti-image fusionmachine learningcomputer vision solutionsdata sciencecomputer visionconvolutional neural networksinformation fusionmachine visionfeature fusiondeep learningfusion learning

Augmented Dataset for Multidimensional Ballast Segmentation and Evaluation. IOP Conference Series Earth and Environmental Science (2024)

K DingJ LuoH HuangJ M HartI I A QamhiaE Tutumluer

deep learningimage representationscene understandingcomputer sciencerailway trackmachine learningballast foulingdata scienceimage classificationdigital image processingmachine visionimage analysisobject detectionaugmented datasetcomputer vision

Augmented Dataset for Vision-Based Analysis of Railroad Ballast via Multi-Dimensional Data Synthesis. Algorithms (2024)

Kelin DingJiayi LuoHaohang HuangJohn M. HartIssam I. A. QamhiaErol Tutumluer

deep learning3d computer visionimage representationballast particle segmentationmachine learning researchscene understandingcomputer sciencemachine learningdata scienceinformation fusionmachine visionimage analysisdeep learning approachesobject detectionaugmented datasetcomputer vision

Towards Automated Field Ballast Condition Evaluation: Field Validation of the Ballast Scanning Vehicle Capabilities. Transportation Geotechnics (2024)

Jiayi LuoKelin DingHaohang HuangIssam I.A. QamhiaErol TutumluerJohn M. HartHugh ThompsonTheodore R. Sussmann

optical image recognitionsystems engineeringstructural health monitoringcivil engineeringmedical image computingautomated inspectionballast scanning vehicledigital image processingmachine visionfield validationdeep learningballast degradation

Deep Learning-Based Segmentation for Field Evaluation of Riprap and Large-Sized Aggregates. Geo-Congress 2019 (2023)

Jiayi LuoHaohang HuangIssam I. A. QamhiaJohn M. HartErol Tutumluer

civil engineeringengineeringdeep learning-based segmentationcomputational imagingmachine learningconvolutional neural networksvisual inspectiondigital image processingmachine visionimage analysisaggregate materialsobject detectionimage segmentationdeep learning

I-Riprap 3D Image Analysis Software: User Manual. (2023)

Haohang HuangJiayi LuoKelin DingErol TutumluerJohn HartIssam Qamhia

3d computer visionriprap rockindividual aggregatescomputer graphicscomputer sciencecomputational imaging3d reconstructioncomputer visioni-riprap 3ddigital image processingmachine visionimage analysis3d modelingdeep learning

Toward Automated Field Ballast Condition Evaluation: Algorithm Development Using a Vision Transformer Framework. Transportation Research Record Journal of the Transportation Research Board (2023)

Jiayi LuoHaohang HuangKelin DingIssam I. A. QamhiaErol TutumluerJohn M. HartHugh ThompsonTheodore R. Sussmann

engineering geologycivil engineeringstructural health monitoringgeotechnical engineeringdeep learning techniquescomputational imagingautomated inspectiondigital image processingedge detectionimage analysisimage segmentation kernelsubjective visual inspectionimage segmentationdeep learning

Toward Automated Field Ballast Condition Evaluation: Development of a Ballast Scanning Vehicle. Transportation Research Record Journal of the Transportation Research Board (2023)

Jiayi LuoKelin DingHaohang HuangJohn M. HartIssam I. A. QamhiaErol TutumluerHugh ThompsonTheodore R. Sussmann

structural engineeringtransportation engineeringsystems engineeringengineeringstructural health monitoringgeotechnical engineeringautomated inspectionvisual inspectionballast scanning vehiclestructural testingballast degradation

3D Image Analysis Using Deep Learning for Size and Shape Characterization of Stockpile Riprap Aggregates—Phase 2. (2022)

Haohang HuangErol TutumluerJiayi LuoKelin DingIssam QamhiaJohn Hart

3d computer visionriprap rockindividual aggregatesdeep learning techniquescomputational imagingdata sciencecomputer vision3d reconstructiondigital image processingmachine visionimage analysisimage segmentationdeep learning

I-Riprap Computer Vision Software for Automated Size and Shape Characterization of Riprap in Stockpile Images. Transportation Research Record Journal of the Transportation Research Board (2021)

Haohang HuangJiayi LuoIssam QamhiaErol TutumluerJohn M. HartAndrew J. Stolba

deep learningimage representationriprap rockscomputer scienceautomated inspectiondata sciencedigital image processingmachine visionimage analysisdeep learning methodsconvolutional neural networkscomputer vision

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John C Hart

Professor

University of Illinois Urbana-Champaign

Affiliations

The Grainger College of Engineering

Siebel School of Computing and Data Science

John C Hart is currently serving as a Siebel School Of Computing And Data Science Professor at University of Illinois Urbana-Champaign.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

John C Hart

University of Illinois Urbana-Champaign

Professor

You can click a keyword to filter the displayed items

Notable Scholarly Works

Notable Federal Grants

Collaborators

I-Ballast: Computer Vision Solutions for Ballast Degradation Analysis Using Deep-Learning and Data Fusion Methods. Geodata and AI. (2025)

Kelin DingJiayi LuoHaohang HuangJohn M. HartIssam I.A. QamhiaErol TutumluerHugh ThompsonTheodore R. Sussmann

Augmented Dataset for Multidimensional Ballast Segmentation and Evaluation. IOP Conference Series Earth and Environmental Science (2024)

K DingJ LuoH HuangJ M HartI I A QamhiaE Tutumluer

Augmented Dataset for Vision-Based Analysis of Railroad Ballast via Multi-Dimensional Data Synthesis. Algorithms (2024)

Kelin DingJiayi LuoHaohang HuangJohn M. HartIssam I. A. QamhiaErol Tutumluer

Towards Automated Field Ballast Condition Evaluation: Field Validation of the Ballast Scanning Vehicle Capabilities. Transportation Geotechnics (2024)

Jiayi LuoKelin DingHaohang HuangIssam I.A. QamhiaErol TutumluerJohn M. HartHugh ThompsonTheodore R. Sussmann

Deep Learning-Based Segmentation for Field Evaluation of Riprap and Large-Sized Aggregates. Geo-Congress 2019 (2023)

Jiayi LuoHaohang HuangIssam I. A. QamhiaJohn M. HartErol Tutumluer

I-Riprap 3D Image Analysis Software: User Manual. (2023)

Haohang HuangJiayi LuoKelin DingErol TutumluerJohn HartIssam Qamhia

Toward Automated Field Ballast Condition Evaluation: Algorithm Development Using a Vision Transformer Framework. Transportation Research Record Journal of the Transportation Research Board (2023)

Jiayi LuoHaohang HuangKelin DingIssam I. A. QamhiaErol TutumluerJohn M. HartHugh ThompsonTheodore R. Sussmann

Toward Automated Field Ballast Condition Evaluation: Development of a Ballast Scanning Vehicle. Transportation Research Record Journal of the Transportation Research Board (2023)

Jiayi LuoKelin DingHaohang HuangJohn M. HartIssam I. A. QamhiaErol TutumluerHugh ThompsonTheodore R. Sussmann

3D Image Analysis Using Deep Learning for Size and Shape Characterization of Stockpile Riprap Aggregates—Phase 2. (2022)

Haohang HuangErol TutumluerJiayi LuoKelin DingIssam QamhiaJohn Hart

I-Riprap Computer Vision Software for Automated Size and Shape Characterization of Riprap in Stockpile Images. Transportation Research Record Journal of the Transportation Research Board (2021)

Haohang HuangJiayi LuoIssam QamhiaErol TutumluerJohn M. HartAndrew J. Stolba

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