Faculty

Institution

Unit

Venue

David P. Woodruff

Professor

Carnegie Mellon University

Affiliations

School of Computer Science

Computer Science Department

David P. Woodruff is currently serving as a Computer Science Professor at Carnegie Mellon University.

Honors

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Experiences

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Education

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David P. Woodruff

Carnegie Mellon University

Professor

You can click a keyword to filter the displayed items

computer science applied mathematics machine learning approximation theory data science mathematical optimization low-rank approximation numerical linear algebra mathematics linear algebra machine learning research streaming data streaming algorithms numerical algorithms computational optimization data streams computational science theoretical computer science stream processing adversarial machine learning numerical analysis scientific computing discrete algorithms combinatorial optimization matrix analysis matrix theory matrix factorization theory of computation dimensionality reduction input sparsity time data streaming architecture estimation theory communication complexity sketch-based modeling kernel methods data stream management supervised learning principal component analysis learning theory tight bounds computational intelligence numerical mathematics data stream mining computational learning theory approximation methods regularization (mathematics) optimization problems mathematical programming robust optimization information theory sublinear algorithms subspace approximation social choice data security databases ranking algorithms quantum algorithms unsupervised machine learning strong coresets neural networks schatten norms distance matrices matrix norms zero-one law quantum-inspired algorithms polynomial kernels kronecker product regression decision science learning analytics automated deduction applied mathematical modelling theoretical prediction secure enclave genomic data analysis goodbye dimension optimal communication-distortion tradeoff data privacy privacy protection computational complexity differential privacy optimal algorithms

Notable Scholarly Works

Notable Federal Grants

Collaborators

Finding Heavy-Hitters With Optimal State Changes. PODS (2026)

mathematical optimizationapplied probabilitycombinatorial optimizationcomputer sciencealgorithmic developmentcomputational optimizationoptimal state changesstochastic optimizationtheoretical computer sciencecomputational science

Learning-Augmented Sketching Offers Improved Performance for Privacy Preserving and Secure Gwas. iScience (2025)

Junyan XuKaiyuan ZhuJieling CaiCan KockanNatnatee DokmaiHyunghoon ChoDavid P WoodruffS Cenk Sahinalp

data securitycomputer sciencedata sciencesecure gwasdata anonymizationprivacy-preserving communicationdata privacybiometricsprivacy preserving

Lifting Linear Sketches: Optimal Bounds and Adversarial Robustness. (2025)

mathematical optimizationlinear sketchescomputer sciencemachine learningadversarial machine learningconvex analysisdeep learning

Online Lewis Weight Sampling. ACM Transactions on Algorithms (2025)

sampling theorystatistical methodologyonline lewis weightmonte carlo samplingstatistical inferencesamplingsampling (statistics)applied statisticsstatistics

Perfect Sampling in Turnstile Streams Beyond Small Moments. Proceedings of the ACM on Management of Data (2025)

perfect samplingsampling (signal processing)applied mathematicssampling theorystatistical physicsapplied probabilitysamplingstreaming algorithms

Tight Sampling Bounds for Eigenvalue Approximation. Society for Industrial and Applied Mathematics eBooks (2025)

approximation theoryconvex analysisasymptotic analysisapplied mathematicsmathematicssampling theorytight sampling boundsrandom matrixsamplinghigh-dimensional statisticsnumerical linear algebramatrix analysis

Adaptive Regret for Bandits Made Possible: Two Queries Suffice. arXiv (Cornell University) (2024)

Lu, ZhouZhang, QiuyiChen, XinyiZhang, FredWoodruff, DavidHazan, Elad

information retrievaladaptive regretquery optimizationcomputer science

A New Information Complexity Measure for Multi-Pass Streaming With Applications. (2024)

Mark BravermanSumegha GargQian LiShuo WangDavid P. WoodruffJiapeng Zhang

digital signal processingcomputer sciencemulti-pass streaming

Approximation Algorithms on Matrices - With Some Database Applications!. (2024)

David P. Woodruff

approximation theorymatrix theoryapplied mathematicsmatrix factorizationcomputer scienceapproximation algorithmsdatabase applicationsmathematicsmatrix analysis

A Strong Separation for Adversarially Robust $\Ell_0$ Estimation for Linear Sketches. arXiv (Cornell University) (2024)

Gribelyuk, ElenaLin, HonghaoWoodruff, David P.Yu, HuachengZhou, Samson

applied mathematicslinear sketchescomputer sciencemachine learningadversarial machine learningdata sciencedeep learning

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David P. Woodruff

Professor

Carnegie Mellon University

Affiliations

School of Computer Science

Computer Science Department

David P. Woodruff is currently serving as a Computer Science Professor at Carnegie Mellon 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

David P. Woodruff

Carnegie Mellon University

Professor

You can click a keyword to filter the displayed items

Notable Scholarly Works

Notable Federal Grants

Collaborators

Finding Heavy-Hitters With Optimal State Changes. PODS (2026)

Learning-Augmented Sketching Offers Improved Performance for Privacy Preserving and Secure Gwas. iScience (2025)

Junyan XuKaiyuan ZhuJieling CaiCan KockanNatnatee DokmaiHyunghoon ChoDavid P WoodruffS Cenk Sahinalp

data securitycomputer sciencedata sciencesecure gwasdata anonymizationprivacy-preserving communicationdata privacybiometricsprivacy preserving

Lifting Linear Sketches: Optimal Bounds and Adversarial Robustness. (2025)

mathematical optimizationlinear sketchescomputer sciencemachine learningadversarial machine learningconvex analysisdeep learning

Online Lewis Weight Sampling. ACM Transactions on Algorithms (2025)

sampling theorystatistical methodologyonline lewis weightmonte carlo samplingstatistical inferencesamplingsampling (statistics)applied statisticsstatistics

Perfect Sampling in Turnstile Streams Beyond Small Moments. Proceedings of the ACM on Management of Data (2025)

perfect samplingsampling (signal processing)applied mathematicssampling theorystatistical physicsapplied probabilitysamplingstreaming algorithms

Tight Sampling Bounds for Eigenvalue Approximation. Society for Industrial and Applied Mathematics eBooks (2025)

Adaptive Regret for Bandits Made Possible: Two Queries Suffice. arXiv (Cornell University) (2024)

Lu, ZhouZhang, QiuyiChen, XinyiZhang, FredWoodruff, DavidHazan, Elad

information retrievaladaptive regretquery optimizationcomputer science

A New Information Complexity Measure for Multi-Pass Streaming With Applications. (2024)

Mark BravermanSumegha GargQian LiShuo WangDavid P. WoodruffJiapeng Zhang

digital signal processingcomputer sciencemulti-pass streaming

Approximation Algorithms on Matrices - With Some Database Applications!. (2024)

David P. Woodruff

approximation theorymatrix theoryapplied mathematicsmatrix factorizationcomputer scienceapproximation algorithmsdatabase applicationsmathematicsmatrix analysis

A Strong Separation for Adversarially Robust $\Ell_0$ Estimation for Linear Sketches. arXiv (Cornell University) (2024)

Gribelyuk, ElenaLin, HonghaoWoodruff, David P.Yu, HuachengZhou, Samson

applied mathematicslinear sketchescomputer sciencemachine learningadversarial machine learningdata sciencedeep learning

1
2
3
4
5
23
10 / page

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numerical linear algebra

discrete algorithm

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University of Illinois Chicago

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philosophy of computer science

Ryan Tibshirani

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quantitative management

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