Faculty

Institution

Unit

Venue

Damek Shea Davis

Associate Professor

Cornell University

Affiliations

College of Engineering

School of Operations Research and Information Engineering

Damek Shea Davis is currently serving as a College Of Engineering Associate Professor at Cornell University.

Honors

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Experiences

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Education

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Damek Shea Davis

Cornell University

Associate Professor

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applied mathematics mathematical optimization computational optimization numerical algorithms computer science convex analysis approximation theory convex optimization nondifferentiable optimization mathematics numerical analysis stochastic optimization stochastic process machine learning variational analysis data science numerical linear algebra numerical mathematics abstract and applied analysis statistical inference large scale optimization mathematical programming computational statistics global optimization convergence analysis computational mathematics machine learning research derivative-free optimization control optimization statistical methodology signal reconstruction weakly convex functions convergence rate parallel programming computational imaging combinatorial optimization image representation machine vision regularization (mathematics) compressive sensing air traffic management stochastic calculus mixture distribution convergence rate analysis moreau envelope composite optimization stochastic differential equations low-rank approximation statistical learning theory mixture analysis scheduling problems vehicle routing problems air traffic control route planning model optimization stochastic model-based minimization subgradient methods monotone inclusions gradient evaluations em algorithm convex functions terminal airspace optimal routing semidefinite programming semi-definite optimization matrix factorization image restoration phase retrieval massively-parallel computing multivariate approximation scheduling analysis signal separation deconvolution three-operator splitting scheme implicit smoothing tame functions scientific computing data mining data optimization optimization-based data mining analytics statistical pattern recognition signal processing

Notable Scholarly Works

Notable Federal Grants

Collaborators

Active Manifolds, Stratifications, and Convergence to Local Minima in Nonsmooth Optimization. Foundations of Computational Mathematics (2025)

Damek DavisDmitriy DrusvyatskiyLiwei Jiang

mathematical optimizationnondifferentiable optimizationabstract and applied analysispde-constrained optimizationnonsmooth optimizationactive manifoldsnumerical algorithmsderivative-free optimizationmathematicsglobal optimizationfunctional analysisnonlinear analysisunconstrained optimizationnumerical analysiscomputational mathematicsvariational analysisgeometric analysiscomputational optimizationlocal minimaapplied mathematics

Clustering a Mixture of Gaussians With Unknown Covariance. Bernoulli (2025)

Damek DavisMateo DíazKaizheng Wang

clusteringgaussian analysismixture analysisapplied mathematicsmixture distributionunknown covariancecomputational statisticsstatistical inferencebayesian analysis

Online Covariance Estimation in Nonsmooth Stochastic Approximation. arXiv (Cornell University) (2025)

Jiang, LiweiRoy, AbhishekBalasubramanian, KrishnaDavis, DamekDrusvyatskiy, DmitriyNa, Sen

mathematical optimizationstatistical methodologyonline covariance estimationestimation theorynonsmooth stochastic approximationconvergence ratestochastic processcomputational statisticsapplied statisticsstatistical inferenceapplied mathematicsstatisticsstochastic optimization

Stochastic Optimization Over Proximally Smooth Sets. SIAM Journal on Optimization (2025)

Damek DavisDmitriy DrusvyatskiyZhan Shi

mathematical optimizationnondifferentiable optimizationnatural stationarity measurefunctional analysisabstract and applied analysisconvex optimizationweakly convex functionsmathematicsvariational analysisrobust optimizationstochastic processconvex analysiscomputational optimizationapproximation theoryapplied mathematicssmooth manifoldsstochastic optimization

A Local Nearly Linearly Convergent First-Order Method for Nonsmooth Functions With Quadratic Growth. Foundations of Computational Mathematics (2024)

Damek DavisLiwei Jiang

nondifferentiable optimizationconvergence analysisabstract and applied analysisnumerical analysisperturbation methodsquadratic growthnumerical mathematicsnonsmooth functionsapproximation theoryapplied mathematicsnumerical algorithms

Asymptotic Normality and Optimality in Nonsmooth Stochastic Approximation. The Annals of Statistics (2024)

Damek DavisDmitriy DrusvyatskiyLiwei Jiang

asymptotic normalityasymptotic analysisstochastic calculusstochastic processconvex analysisapplied mathematics

Computational Microscopy Beyond Perfect Lenses. Physical review. E (2024)

Xingyuan LuMinh PhamElisa NegriniDamek DavisStanley J. OsherJianwei Miao

biophysicsmicroscopyoptical imagingbiological imagingdiffractive opticscomputational microscopybiophotonicsradiologycomputational imagingquantitative phase imagingmicroscopy methodssitu cdiophthalmologylight microscopyperfect lensesbiomedical imaging

Global Optimality of the Em Algorithm for Mixtures of Two-Component Linear Regressions. IEEE Transactions on Information Theory (2024)

Jeongyeol KwonWei QianYudong ChenConstantine CaramanisDamek DavisNhat Ho

mathematical optimizationoptimization problemsem algorithmglobal optimalityestimation theorymixture distributiontwo-component linear regressionscomputational statisticscomputational optimizationnumerical linear algebraapplied statisticsstatistical inferenceapplied mathematicsstatisticsnumerical algorithms

Gradient Descent With Adaptive Stepsize Converges (Nearly) Linearly Under Fourth-Order Growth. arXiv (Cornell University) (2024)

Davis, DamekDrusvyatskiy, DmitriyJiang, Liwei

mathematical optimizationcomputer scienceneural computationconvergence analysisadaptive stepsizederivative-free optimizationconstant order growthmachine learning researchadaptive optimizationcomputational optimizationgradient descentlarge scale optimizationapplied mathematicsmachine learningnumerical algorithms

Aiming Towards the Minimizers: Fast Convergence of Sgd for Overparametrized Problems. arXiv (Cornell University) (2023)

Liu, ChaoyueDrusvyatskiy, DmitriyBelkin, MikhailDavis, DamekMa, Yi-An

mathematical optimizationcomputer sciencemodel optimizationregularity conditiondeep learningneural network (machine learning)machine learning researchcomputational intelligencedata sciencecomputational optimizationconvex analysisadaptive optimizationinterpolation regimelarge scale optimizationapproximation theoryapplied mathematicsmachine learningnumerical algorithms

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Damek Shea Davis

Associate Professor

Cornell University

Affiliations

College of Engineering

School of Operations Research and Information Engineering

Damek Shea Davis is currently serving as a College Of Engineering Associate Professor at Cornell University.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

Damek Shea Davis

Cornell University

Associate Professor

You can click a keyword to filter the displayed items

Notable Scholarly Works

Notable Federal Grants

Collaborators

Active Manifolds, Stratifications, and Convergence to Local Minima in Nonsmooth Optimization. Foundations of Computational Mathematics (2025)

Damek DavisDmitriy DrusvyatskiyLiwei Jiang

Clustering a Mixture of Gaussians With Unknown Covariance. Bernoulli (2025)

Damek DavisMateo DíazKaizheng Wang

clusteringgaussian analysismixture analysisapplied mathematicsmixture distributionunknown covariancecomputational statisticsstatistical inferencebayesian analysis

Online Covariance Estimation in Nonsmooth Stochastic Approximation. arXiv (Cornell University) (2025)

Jiang, LiweiRoy, AbhishekBalasubramanian, KrishnaDavis, DamekDrusvyatskiy, DmitriyNa, Sen

Stochastic Optimization Over Proximally Smooth Sets. SIAM Journal on Optimization (2025)

Damek DavisDmitriy DrusvyatskiyZhan Shi

A Local Nearly Linearly Convergent First-Order Method for Nonsmooth Functions With Quadratic Growth. Foundations of Computational Mathematics (2024)

Damek DavisLiwei Jiang

Asymptotic Normality and Optimality in Nonsmooth Stochastic Approximation. The Annals of Statistics (2024)

Damek DavisDmitriy DrusvyatskiyLiwei Jiang

asymptotic normalityasymptotic analysisstochastic calculusstochastic processconvex analysisapplied mathematics

Computational Microscopy Beyond Perfect Lenses. Physical review. E (2024)

Xingyuan LuMinh PhamElisa NegriniDamek DavisStanley J. OsherJianwei Miao

Global Optimality of the Em Algorithm for Mixtures of Two-Component Linear Regressions. IEEE Transactions on Information Theory (2024)

Jeongyeol KwonWei QianYudong ChenConstantine CaramanisDamek DavisNhat Ho

Gradient Descent With Adaptive Stepsize Converges (Nearly) Linearly Under Fourth-Order Growth. arXiv (Cornell University) (2024)

Davis, DamekDrusvyatskiy, DmitriyJiang, Liwei

Aiming Towards the Minimizers: Fast Convergence of Sgd for Overparametrized Problems. arXiv (Cornell University) (2023)

Liu, ChaoyueDrusvyatskiy, DmitriyBelkin, MikhailDavis, DamekMa, Yi-An

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