Faculty

Institution

Unit

Venue

Ivan Dokmanic

Adjunct Associate Professor

University of Illinois Urbana-Champaign

Affiliations

The Grainger College of Engineering

Department of Electrical and Computer Engineering

Ivan Dokmanic is currently serving as an Electrical And Computer Engineering Adjunct Associate Professor at University of Illinois Urbana-Champaign.

Honors

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Experiences

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Education

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Ivan Dokmanic

University of Illinois Urbana-Champaign

Adjunct Associate Professor

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applied mathematics inverse problems signal processing computer science computational imaging machine learning localization data science acoustic signal processing sound machine learning research numerical algorithms image representation image analysis speaker localization mathematics digital signal processing numerical linear algebra speech processing biomedical imaging signal reconstruction convex analysis mathematical optimization image reconstruction computational geometry medical image computing convolutional neural networks geometric learning machine vision spatial audio array processing reconstruction techniques information fusion computational statistics computational optimization localization technique matrix theory matrix analysis 3d reconstruction inverse scattering transforms convex optimization manifold learning microphone array nonlinear dimensionality reduction sparse representations feature learning sampling (signal processing) random matrix euclidean distance matrices acoustic echoes simultaneous localization point source model unknown view tomography field robotics wireless communications multidimensional signal processing acoustical engineering architectural acoustics beamforming multi-channel processing data augmentation matrix factorization compressive sensing matrix methods low-rank approximation multi-view geometry signal processing community room geometry inverse problem unknown vector sparse pseudoinverse matrix norms multipath-enabled private audio essential theory software package python package cyberphysical systems technology informatics computational thinking computational science intelligent computing cognitive informatics memetic computing audio processing advanced intelligent system

Notable Scholarly Works

Notable Federal Grants

Collaborators

End-To-End Localized Deep Learning for Cryo-Et. arXiv (Cornell University) (2025)

Kishore, VinithDebarnot, ValentinRighetto, Ricardo D.Khorashadizadeh, AmirEhsanDokmanić, Ivan

transform-domain localityconvolutional neural networksgeometric learningdeep learningbiological imagingmedical imagingnetwork robustbiomedical imagingcomputational imagingcryo-electron tomographybiomedical engineeringdata sciencemachine learning

GLIMPSE: Generalized Locality for Scalable and Robust Ct. IEEE Transactions on Medical Imaging (2025)

AmirEhsan KhorashadizadehValentin DebarnotTianlin LiuIvan Dokmanić

convolutional neural networksdeep learningrobust ctimage reconstructionprojection orientationsmedical imagingcomputed tomographybiomedical imagingradiologyneural network (machine learning)digital image processingimage representationimage analysismachine learning

LOFI: Neural Local Fields for Scalable Image Reconstruction. IEEE Transactions on Computational Imaging (2025)

AmirEhsan KhorashadizadehTobías I. LiaudatTianlin LiuJason D. McEwenIvan Dokmanić

scene modelingscalable image reconstructioncomputer visioncomputational imagingdigital image processingmachine visionimage representationimage analysisbiomedical imaging

Spring-Block Theory of Feature Learning in Deep Neural Networks. Physical Review Letters (2025)

Cheng ShiLiming PanIvan Dokmanić

nonlinear phenomenaneural computationmacroscopic mechanical theorygeometric learningdeep learningphysicsneurosciencenonlinear dynamicsspring-block theoryfeature learningneural network (machine learning)machine learning researchbrain-like computingcomputational neuroscienceneuronal networksapplied mathematicsmachine learning

A Graph Dynamics Prior for Relational Inference. Proceedings of the AAAI Conference on Artificial Intelligence (2024)

Liming PanCheng ShiIvan Dokmanic

computer sciencegraph theorygraph processinginferencegraph dynamicsneural network (machine learning)graph neural networksmachine learning researchcomputational intelligencedata sciencerelational inferencegraph dynamics priormachine learning

A Spring-Block Theory of Feature Learning in Deep Neural Networks. arXiv (Cornell University) (2024)

Shi, ChengPan, LimingDokmanić, Ivan

computer sciencephysic aware machine learningdeep learningsparse neural networkspring-block theoryfeature learningneural network (machine learning)machine learning researchcomputational intelligencephase diagramapplied mathematicsmachine learning

GLIMPSE: Generalized Local Imaging With Mlps. arXiv (Cornell University) (2024)

Khorashadizadeh, AmirEhsanDebarnot, ValentinLiu, TianlinDokmanić, Ivan

medical image computingconvolutional neural networkspoor generalizationcomputer visiondeep learningimage reconstructionmedical imagingradiologycomputational imagingneural network (machine learning)digital image processingmachine learning researchgeneralized local imagingimage representationimage analysisbiomedical imaging

Homophily Modulates Double Descent Generalization in Graph Convolution Networks. Proceedings of the National Academy of Sciences (2024)

Cheng ShiLiming PanHong HuIvan Dokmanić

computer scienceneural computationgraph theorygeometric learninggraph processingdouble descent generalizationdouble descentneural network (machine learning)graph neural networksmachine learning researchcomputational intelligencedata sciencecomputational statisticsgraph analysisnetwork sciencemachine learning

Ice-Tide: Implicit Cryo-Et Imaging and Deformation Estimation. arXiv (Cornell University) (2024)

Debarnot, ValentinKishore, VinithRighetto, Ricardo D.Dokmanić, Ivan

reconstruction techniquesmicroscopyadvanced imagingphysicsimage reconstructiontilt seriescomputational imaging3d imagingcryogenic electron tomographydigital image processingdeformation estimationinverse problemsplanetary sciencesbiomedical imaging

Injectivity of Relu Networks: Perspectives From Statistical Physics. Applied and Computational Harmonic Analysis (2024)

Antoine MaillardAfonso S. BandeiraDavid BeliusIvan DokmanićShuta Nakajima

statistical mechanicsneural computationstatistical physicstheoretical physicsmathematicsrelu networksmathematical statistical physicapplied mathematicsmathematical sciencesstatistical field theories

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Ivan Dokmanic

Adjunct Associate Professor

University of Illinois Urbana-Champaign

Affiliations

The Grainger College of Engineering

Department of Electrical and Computer Engineering

Ivan Dokmanic is currently serving as an Electrical And Computer Engineering Adjunct Associate 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

Ivan Dokmanic

University of Illinois Urbana-Champaign

Adjunct Associate Professor

You can click a keyword to filter the displayed items

Notable Scholarly Works

Notable Federal Grants

Collaborators

End-To-End Localized Deep Learning for Cryo-Et. arXiv (Cornell University) (2025)

Kishore, VinithDebarnot, ValentinRighetto, Ricardo D.Khorashadizadeh, AmirEhsanDokmanić, Ivan

GLIMPSE: Generalized Locality for Scalable and Robust Ct. IEEE Transactions on Medical Imaging (2025)

AmirEhsan KhorashadizadehValentin DebarnotTianlin LiuIvan Dokmanić

LOFI: Neural Local Fields for Scalable Image Reconstruction. IEEE Transactions on Computational Imaging (2025)

AmirEhsan KhorashadizadehTobías I. LiaudatTianlin LiuJason D. McEwenIvan Dokmanić

scene modelingscalable image reconstructioncomputer visioncomputational imagingdigital image processingmachine visionimage representationimage analysisbiomedical imaging

Spring-Block Theory of Feature Learning in Deep Neural Networks. Physical Review Letters (2025)

Cheng ShiLiming PanIvan Dokmanić

A Graph Dynamics Prior for Relational Inference. Proceedings of the AAAI Conference on Artificial Intelligence (2024)

Liming PanCheng ShiIvan Dokmanic

A Spring-Block Theory of Feature Learning in Deep Neural Networks. arXiv (Cornell University) (2024)

Shi, ChengPan, LimingDokmanić, Ivan

GLIMPSE: Generalized Local Imaging With Mlps. arXiv (Cornell University) (2024)

Khorashadizadeh, AmirEhsanDebarnot, ValentinLiu, TianlinDokmanić, Ivan

Homophily Modulates Double Descent Generalization in Graph Convolution Networks. Proceedings of the National Academy of Sciences (2024)

Cheng ShiLiming PanHong HuIvan Dokmanić

Ice-Tide: Implicit Cryo-Et Imaging and Deformation Estimation. arXiv (Cornell University) (2024)

Debarnot, ValentinKishore, VinithRighetto, Ricardo D.Dokmanić, Ivan

Injectivity of Relu Networks: Perspectives From Statistical Physics. Applied and Computational Harmonic Analysis (2024)

Antoine MaillardAfonso S. BandeiraDavid BeliusIvan DokmanićShuta Nakajima

statistical mechanicsneural computationstatistical physicstheoretical physicsmathematicsrelu networksmathematical statistical physicapplied mathematicsmathematical sciencesstatistical field theories

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