Ronald Coifman, PhD
Sterling Professor of Mathematics and Professor of Electrical EngineeringCards
Contact Info
About
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 .
Appointments
Electrical Engineering
ProfessorFully Joint
Other Departments & Organizations
Education & Training
- PhD
- University of Geneva (1965)
Research
Overview
Professor Coifman is currently developing
analysis tools for massive medical signatures analysis, such as spectrometric diagnostics and hyperspectral imaging.
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
242Publications
22,505Citations
Publications
2024
Estimating 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 ResearchAltmetricConceptsKernel-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, 1-11. PMID: 38580861, DOI: 10.1038/s41587-024-02186-3.Peer-Reviewed Original ResearchAltmetricConceptsGene 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
Robust 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
2022
Multiscale Decompositions of Hardy Spaces
Coifman R, Peyrière J. Multiscale Decompositions of Hardy Spaces. Applied And Numerical Harmonic Analysis 2022, 445-462. DOI: 10.1007/978-3-030-45847-8_20.Peer-Reviewed Original ResearchCitationsA Common Variable Minimax Theorem for Graphs
Coifman R, Marshall N, Steinerberger S. A Common Variable Minimax Theorem for Graphs. Foundations Of Computational Mathematics 2022, 23: 493-517. DOI: 10.1007/s10208-022-09558-8.Peer-Reviewed Original ResearchCitationsAltmetric
2021
Wavelets and adapted waveform analysis
Coifman R, Wickerhauser M. Wavelets and adapted waveform analysis. 2021, 399-423. DOI: 10.1201/9781003210450-12.Peer-Reviewed Original ResearchCitationsDiffusion Earth Mover's Distance and Distribution Embeddings.
Tong A, Huguet G, Natik A, MacDonald K, Kuchroo M, Coifman R, Wolf G, Krishnaswamy S. Diffusion Earth Mover's Distance and Distribution Embeddings. ArXiv 2021 PMID: 33655017, PMCID: PMC7924278.Peer-Reviewed Original ResearchDoubly Stochastic Normalization of the Gaussian Kernel Is Robust to Heteroskedastic Noise.
Landa B, Coifman RR, Kluger Y. Doubly Stochastic Normalization of the Gaussian Kernel Is Robust to Heteroskedastic Noise. SIAM Journal On Mathematics Of Data Science 2021, 3: 388-413. PMID: 34124607, PMCID: PMC8194191, DOI: 10.1137/20m1342124.Peer-Reviewed Original ResearchCitationsAltmetricConceptsStochastic normalizationHeteroskedastic noiseGaussian kernelHigh-dimensional settingsMatrix convergesAmbient dimensionDifferent noise variancesEuclidean spaceData pointsNoise varianceSymmetric normalizationCertain normalizationAffinity matrixClean counterpartsPairwise distancesKernelNoiseData analysis techniqueSingle-cell RNA-sequencing dataParticular directionSpaceWidespread approachConvergesMatrixHeteroskedasticity
Academic Achievements and Community Involvement
honor Rolf Schock prize 2018
International AwardSwedish Academy of ScienceDetails10/09/2018Sweden
Links & Media
News
- August 07, 2020
Emily Gilmore, MD & ELECTRO-BOOST Team Awarded $3.25M NINDS Grant
- December 15, 2019
Kavli Workshop on Jan. 8: "Current Perspectives on the Generation and Analysis of Complex Data in Neuroscience"
- October 25, 2017
Putting the precise in precision medicine
- October 25, 2017Source: Yale Medicine Magazine
Putting the precise in precision medicine