Ronald Coifman, PhD
Sterling Professor of Mathematics and Professor of Electrical EngineeringCards
Contact Info
About
Copy Link
Titles
Sterling Professor of Mathematics and Professor of Electrical Engineering
Biography
Coifman is a member of the American Academy of Arts and Sciences, the
Connecticut Academy of Science and Engineering, and the National Academy
of Sciences. He is a recipient of the 1996 DARPA Sustained Excellence
Award, the 1996 Connecticut Science Medal, the 1999 Pioneer Award of the
International Society for Industrial and Applied Science, and the 1999
National Medal of Science .
Last Updated on April 07, 2025.
Appointments
Electrical Engineering
ProfessorFully JointStatistics
ProfessorSecondary
Other Departments & Organizations
Education & Training
- PhD
- University of Geneva (1965)
Research
Copy Link
Overview
Professor Coifman is currently developing
analysis tools for massive medical signatures analysis, such as spectrometric diagnostics and hyperspectral imaging.
ORCID
0000-0001-7336-7784
Research at a Glance
Yale Co-Authors
Frequent collaborators of Ronald Coifman's published research.
Publications Timeline
A big-picture view of Ronald Coifman's research output by year.
Gordon Weiss, MD
Hitten Zaveri, PhD
Andreas Coppi
Frederick Warner, PhD
Harlan Krumholz, MD, SM
David van Dijk, PhD, MSc, BSc
247Publications
24,532Citations
Publications
2025
From clutter to clarity: Emergent neural operators via questionnaire metrics
Georgiou A, Manoj A, Su P, Coifman R, Kevrekidis I, Goswami S. From clutter to clarity: Emergent neural operators via questionnaire metrics. Computers & Chemical Engineering 2025, 201: 109201. DOI: 10.1016/j.compchemeng.2025.109201.Peer-Reviewed Original ResearchConceptsAdvanced deep learning architecturesReal-world datasetsDeep learning architectureAgent-based systemsSupervised learning modelsAdvection-diffusion partial differential equationLearning architectureScrambled dataLearning techniquesData-driven system identificationNeural operationsEfficient emulationGenerative modelLearning modelsParameter embeddingDatasetFramework’s potentialSystem identificationClutter dataSystem dynamicsDifferential equationsFrameworkPartial differential equationsEmbeddingArchitectureOn Complex Analytic Tools, and the Holomorphic Rotation Methods
Coifman R, Peyrière J, Weiss G. On Complex Analytic Tools, and the Holomorphic Rotation Methods. Applied And Numerical Harmonic Analysis 2025, 145-161. DOI: 10.1007/978-3-031-76793-7_7.Peer-Reviewed Original ResearchFrom disorganized data to emergent dynamic models: Questionnaires to partial differential equations
Sroczynski D, Kemeth F, Georgiou A, Coifman R, Kevrekidis I. From disorganized data to emergent dynamic models: Questionnaires to partial differential equations. PNAS Nexus 2025, 4: pgaf018. PMID: 39898180, PMCID: PMC11786195, DOI: 10.1093/pnasnexus/pgaf018.Peer-Reviewed Original ResearchConceptsComplex dynamical network modelData-driven derivationData-driven wayDisorganized dataMachine learningPartial differential equationsNetwork modelType of dataEvolutionary partial differential equationsDiffusion mapsDynamic network modelEvolution equationsEmbedded geometryEvolving systemSymmetry breakingTensor typeDifferential equationsTranslational invarianceDerivation of parametersPDE modelAdvection-diffusion modelSmooth parametrization
2024
On learning what to learn: Heterogeneous observations of dynamics and establishing possibly causal relations among them
Sroczynski D, Dietrich F, Koronaki E, Talmon R, Coifman R, Bollt E, Kevrekidis I. On learning what to learn: Heterogeneous observations of dynamics and establishing possibly causal relations among them. PNAS Nexus 2024, 3: pgae494. PMID: 39660076, PMCID: PMC11630787, DOI: 10.1093/pnasnexus/pgae494.Peer-Reviewed Original ResearchEstimating Position-Dependent and Anisotropic Diffusivity Tensors from Molecular Dynamics Trajectories: Existing Methods and Future Outlook
Domingues T, Coifman R, Haji-Akbari A. Estimating Position-Dependent and Anisotropic Diffusivity Tensors from Molecular Dynamics Trajectories: Existing Methods and Future Outlook. Journal Of Chemical Theory And Computation 2024, 20: 4427-4455. PMID: 38815171, DOI: 10.1021/acs.jctc.4c00148.Peer-Reviewed Original ResearchCitationsAltmetricConceptsKernel-based methodsMolecular dynamicsMolecular dynamics trajectoriesAnisotropic diffusion tensorPhysicochemical properties of materialsClosed-form analytical solutionMD trajectoriesMobility statisticsComputational chemistryHeuristic extensionMD simulationsProperties of materialsAlgorithmDynamics trajectoriesDiffusion tensorEstimated diffusivityVariable spaceMaterial propertiesDiscretization techniqueNatural extensionPosition-dependentFokker-Planck equationSpatial binsAnalytical solutionTracer particlesGene trajectory inference for single-cell data by optimal transport metrics
Qu R, Cheng X, Sefik E, Stanley III J, Landa B, Strino F, Platt S, Garritano J, Odell I, Coifman R, Flavell R, Myung P, Kluger Y. Gene trajectory inference for single-cell data by optimal transport metrics. Nature Biotechnology 2024, 43: 258-268. PMID: 38580861, PMCID: PMC11452571, DOI: 10.1038/s41587-024-02186-3.Peer-Reviewed Original ResearchCitationsAltmetricConceptsGene dynamicsGene programTrajectory inferenceBiological processesCell-cell graphDynamics of genesCell trajectory inferenceSingle-cell RNA sequencingSingle-cell dataCell state transitionsMyeloid lineage maturationDynamics of biological processesGene distributionRNA sequencingPseudotemporal orderingGene processingTrajectories of cellsGenesActivity of biological processesTechnical noiseGroups of cellsLineage maturationCellsConstruct cellsSequence
2023
Rapid fluctuations in functional connectivity of cortical networks encode spontaneous behavior
Benisty H, Barson D, Moberly A, Lohani S, Tang L, Coifman R, Crair M, Mishne G, Cardin J, Higley M. Rapid fluctuations in functional connectivity of cortical networks encode spontaneous behavior. Nature Neuroscience 2023, 27: 148-158. PMID: 38036743, PMCID: PMC11316935, DOI: 10.1038/s41593-023-01498-y.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsFunctional connectivitySpontaneous behaviorCortical networksCortical network activityTime-varying functional connectivityFunctional magnetic resonanceCerebral cortexAwake miceDynamic functional connectivityAwake animalsNeighboring neuronsPatterned activityDistinct behavioral statesTwo-photon microscopyNeural activityCortical signalsBehavioral statesCortexNetwork activityCortical dynamicsMagnetic resonanceRobust Estimation of Position-Dependent Anisotropic Diffusivity Tensors from Molecular Dynamics Trajectories
Domingues T, Coifman R, Haji-Akbari A. Robust Estimation of Position-Dependent Anisotropic Diffusivity Tensors from Molecular Dynamics Trajectories. The Journal Of Physical Chemistry B 2023, 127: 8644-8659. PMID: 37757480, DOI: 10.1021/acs.jpcb.3c03581.Peer-Reviewed Original ResearchCitationsAltmetricConceptsMechanical observablesDiffusivity tensorEfficient correction schemeAnisotropic diffusivity tensorStochastic counterpartSame qualitative featuresStochastic trajectoriesVan Hove correlation functionRobust estimationCovariance estimatorMolecular simulation communityCorrelation functionsDiffusivity profilesRotational symmetryLennard-Jones fluidEstimatorQualitative featuresDiffusion mapsSpatial profileObservablesTensorCorrection schemeTransport propertiesProperty functionsPrevious paperRobust Estimation of Position-Dependent Anisotropic Diffusivity Tensors from Stochastic Trajectories
Domingues T, Coifman R, Haji-Akbari A. Robust Estimation of Position-Dependent Anisotropic Diffusivity Tensors from Stochastic Trajectories. The Journal Of Physical Chemistry B 2023, 127: 5273-5287. PMID: 37261948, DOI: 10.1021/acs.jpcb.3c00670.Peer-Reviewed Original ResearchCitationsAltmetricConceptsTime discretizationStochastic trajectoriesMechanical observablesDiffusivity tensorAnisotropic diffusivity tensorPointwise estimatesRigorous generalizationRobust estimationCovariance estimatorDifferent functional formsLocal covarianceKernel-based approachEstimatorFunctional estimatesDiscretizationFunctional formOrthogonal functionsBulk systemKernel functionConfined systemSuch methodsObservablesTensorTransport propertiesCovariance-based estimatorGuido L. Weiss (1928-2021)
Hernández E, Wilson E, Coifman R, Maggioni M, Meyer Y, Ricci F, Šikić H, Soria F, Tabacco A, Torres R. Guido L. Weiss (1928-2021). Notices Of The American Mathematical Society 2023, 70: 1. DOI: 10.1090/noti2607.Peer-Reviewed Original Research
Academic Achievements & Community Involvement
Copy Link
Honors
honor Rolf Schock prize 2018
10/09/2018International AwardSwedish Academy of ScienceDetailsSweden
Get In Touch
Copy Link