Steven Zucker
David and Lucille Packard Professor of Computer Science and Professor of Biomedical EngineeringDownloadHi-Res Photo
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David and Lucille Packard Professor of Computer Science and Professor of Biomedical Engineering
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- Computational Biology and Biomedical Informatics
- Interdepartmental Neuroscience Program
- Neuroscience Track
- Statistics
- Swartz Program in Theoretical Neurobiology
- Wu Tsai Institute
- Yale Combined Program in the Biological and Biomedical Sciences (BBS)
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Overview
Medical Research Interests
Biomedical Engineering; Biomedical Research; Computers; Mathematical Computing; Mathematics; Neurophysiology; Neurosciences; Robotics
ORCID
0000-0002-2205-6895- View Lab Website
Zucker Homepage
Research at a Glance
Yale Co-Authors
Frequent collaborators of Steven Zucker's published research.
Publications Timeline
A big-picture view of Steven Zucker's research output by year.
Ronald Coifman, PhD
9Publications
55Citations
Publications
2025
Individuation of 3D Perceptual Units from Neurogeometry of Binocular Cells
Bolelli M, Citti G, Sarti A, Zucker S. Individuation of 3D Perceptual Units from Neurogeometry of Binocular Cells. SIAM Journal On Imaging Sciences 2025, 18: 2605-2640. DOI: 10.1137/24m1712333.Peer-Reviewed Original ResearchOrientation fields predict human perception of 3D shape from shading
Aubuchon C, Vergne R, Cholewiak S, Kunsberg B, Holtmann-Rice D, Zucker S, Fleming R. Orientation fields predict human perception of 3D shape from shading. Proceedings Of The National Academy Of Sciences Of The United States Of America 2025, 122: e2503088122. PMID: 40638088, PMCID: PMC12280972, DOI: 10.1073/pnas.2503088122.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsHuman perceptionPerception of 3D shapeThree-dimensional structure of surfacesSurface curvature propertiesSurface normalsImage modificationDepth cuesShading objectsOrientation fieldImage orientationLuminance valuesShape perceptionRetinal imagesVisual neuronsImagesLuminanceCurvature propertiesStructure of surfacesLight-variations
2024
Population encoding of stimulus features along the visual hierarchy
Dyballa L, Rudzite A, Hoseini M, Thapa M, Stryker M, Field G, Zucker S. Population encoding of stimulus features along the visual hierarchy. Proceedings Of The National Academy Of Sciences Of The United States Of America 2024, 121: e2317773121. PMID: 38227668, PMCID: PMC10823231, DOI: 10.1073/pnas.2317773121.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsPartitioning feature spaceConvolutional neural networkNeural populationsDiverse visual featuresBattery of visual stimuliManifold embedding techniquesMachine learning approachFeature spaceEncoded featuresVisual featuresNeural networkProperties of individual neuronsPrimary visual cortexPopulation encodingEmbedding techniqueLearning approachPartitioning featuresVisual hierarchyContinuous representationV1 populationsStimulus spaceMulti-electrode arrayGroups of neuronsIndividual neuronsVisual cortexGood continuation in 3D: the neurogeometry of stereo vision
Bolelli M, Citti G, Sarti A, Zucker S. Good continuation in 3D: the neurogeometry of stereo vision. Frontiers In Computer Science 2024, 5: 1142621. PMID: 36713236, PMCID: PMC9882572, DOI: 10.3389/fcomp.2023.1142621.Peer-Reviewed Original ResearchCitationsAltmetric
2023
Connectionisn and the Computational Neurobiology of Curve Detection
Zucker S, Dobbins A, Iverson L. Connectionisn and the Computational Neurobiology of Curve Detection. 2023, 277-296. DOI: 10.1093/oso/9780195076653.003.0009.Peer-Reviewed Original ResearchCitationsConceptsCurve detectionComputational visionOrientation informationReceptive fieldsStereoscopic perceptionComputational neurobiologySame receptive fieldVisionAreas of visionFirst paradigmNearby curvesDetectionSimilar notionsRetinal samplingAbstract OneQuantizationParadigmEnd resultInformationExampleModem theory
2013
Predicting the effects of illumination in shape from shading
Fleming R, Vergne R, Zucker S. Predicting the effects of illumination in shape from shading. Journal Of Vision 2013, 13: 611-611. DOI: 10.1167/13.9.611.Peer-Reviewed Original ResearchCitations
2007
Diffusion Maps and Geometric Harmonics for Automatic Target Recognition (ATR). Volume 2. Appendices
Zucker S, Coifman R. Diffusion Maps and Geometric Harmonics for Automatic Target Recognition (ATR). Volume 2. Appendices. 2007 DOI: 10.21236/ada476152.Peer-Reviewed Original ResearchCitationsConceptsAutomatic target recognitionIntegration of audioGeometric harmonicsLow-dimensional Euclidean spaceVideo streamsAudio streamAutomatic recognitionSimilarity measureDifferent sensorsTarget recognitionDiffusion mapsFirst versionProblem formulationEuclidean coordinatesMeasurement spaceSignal interpretationRecognitionWright-Patterson Air Force BaseAudioEuclidean spaceSoftwareStreamsAFRLDimensional Euclidean spaceSpace
2005
Geometric diffusions for the analysis of data from sensor networks
Coifman RR, Maggioni M, Zucker SW, Kevrekidis IG. Geometric diffusions for the analysis of data from sensor networks. Current Opinion In Neurobiology 2005, 15: 576-584. PMID: 16150587, DOI: 10.1016/j.conb.2005.08.012.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsConceptsSensor networksGeometric diffusionMathematical developmentComplex data setsHarmonic analysisNeural information processingActivity datasetsCertain analogyComputer modelingData setsInformation processingManifoldNetworkModelingGraphData analysisAlgorithmNew toolDatasetAnalysis of dataAnalogyField
2004
Hue geometry and horizontal connections
Ben-Shahar O, Zucker SW. Hue geometry and horizontal connections. Neural Networks 2004, 17: 753-771. PMID: 15288896, DOI: 10.1016/j.neunet.2004.03.011.Peer-Reviewed Original ResearchCitations
Academic Achievements & Community Involvement
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Activities
activity Computer Vision
01/01/2007 - PresentResearchDetailsCanada; ItalyAbstract/SynopsisProfessor Zucker has collaborations with international colleagues in the area of computer vision, in particular in the mathematical and computational description of visual shape.
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