Faculty

Institution

Unit

Venue

Pavlo Krokhmal

University of Arizona

Affiliations

Mathematics

Applied Mathematics

College of Engineering

Systems and Industrial Engineering

College of Science

Mathematics

NonePavlo Krokhmal is currently serving as a Applied Mathematics faculty at University of Arizona.

Honors

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Experiences

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Education

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Pavlo Krokhmal

University of Arizona

You can click a keyword to filter the displayed items

applied mathematics risk management mathematical optimization finance computer science operations research machine learning combinatorial optimization network science engineering optimization problems mathematical finance investment management mathematical programming engineering optimization computational optimization stochastic optimization portfolio optimization discrete optimization uncertainty analysis decision science quantitative management network theory temporal changes multidimensional assignment problem stochastic programs hedge fund portfolios logistics system safety control optimization constrained optimization empirical finance linear programming change detection high uncertainty model optimization combinatorial optimization problems hypergraph matchings arbitrary networks economic modelling scientific computing biomedical informatics thermal engineering policy modeling vibration control structural optimization risk metrics risk model validation risk analysis (business) financial risk management biomedical data analysis uncertainty formalism uncertainty management real-time monitoring online algorithms signal detection financial modeling continuous optimization graphology graph analysis collaborative search applied mathematical modelling capacity planning energy production power engineering grid optimization power system optimization conditional value-at-risk objective random assignment problems p-order conic constraints risk optimization psychophysiological data local minima robust decision making certainty equivalent measures asymptotic behavior probabilistic system decision making systems engineering multidisciplinary optimization uncertainty quantification financial engineering

Notable Scholarly Works

Notable Federal Grants

Collaborators

Comparisons of Unsupervised and Supervised Machine Learning Algorithms for Prediction of Damage in Composites From 3D Micro-Ct Images. (2025)

micro-ct imagescomputer-aided diagnosisbiomedical imagingmedical image computingmachine learning researchmedical image analysismachine learningdamage mechanismdata sciencedigital image processingradiologyimage analysismedical imagingmechanical engineering

Reformulation Techniques for Chance-Constrained Combinatorial Optimization Problems. Springer eBooks (2025)

mathematical optimizationapplied mathematicsapplied probabilitycombinatoricscombinatorial optimizationcomputer sciencecomputational optimizationdiscrete optimizationreformulation techniquesoperations researchcombinatorial problemsoptimization problems

Minimizing the Influence Spread Over a Network Through Node Interception. Optimization Letters (2024)

Shunyu YaoNeng FanPavlo Krokhmal

mathematical optimizationnetwork analysisnode interceptionnetwork optimizationapplied mathematicsinfluence spreadinfluence model

Unsupervised Machine Learning for Automatic Image Segmentation of Impact Damage in Cfrp Composites. Applied Composite Materials (2024)

Olesya ZhupanskaPavlo Krokhmal

composite technologycomposite materialsunsupervised machine learningcomposite sciencematerials engineeringautomatic image segmentationmachine learningmaterials scienceapplied physicsimpact damagecfrp compositesimage segmentationmechanical engineering

Asymptotic Bounds for Clustering Problems in Random Graphs. Networks (2023)

Eugene LykhovydSergiy ButenkoPavlo Krokhmal

network scienceclusteringdata sciencegraph theorynetwork theoryasymptotic bounds

PREFACE: Special Issue of Moa 2020. Journal of Global Optimization (2023)

Ya-Feng LiuZi XuPavlo A. KrokhmalJiming Peng

applied mathematicslarge-scale global optimizationspecial issueoperations researchglobal optimization

Risk‐Averse Optimization and Resilient Network Flows. Networks (2023)

Masoud EshghaliPavlo A. Krokhmal

network scienceresilient network flowssystems engineeringrisk-averse optimization

Stochastic and Risk Averse Maximum Subgraph Problems. Encyclopedia of Optimization (2022)

Masoud EshghaliMaciej RyszPavlo Krokhmal

graph theoryapplied mathematics

Unsupervised Machine Learning Algorithms for Analysis of Low Velocity Impact Damage in Composite Structures From Ct Image Data. (2022)

Olesya I. ZhupanskaPavlo A. Krokhmal

unsupervised machine learningengineeringstructural analysismachine learningmaterials sciencect image dataimage analysiscomputed tomographymechanical engineering

A Scalable Markov Chain Framework for Influence Maximization in Arbitrary Networks. IEEE Transactions on Network Science and Engineering (2021)

Juan S. BorreroMajid AkhgarPavlo A. Krokhmal

network sciencearbitrary networkssystems engineeringinfluence maximization

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Pavlo Krokhmal

University of Arizona

Affiliations

Mathematics

Applied Mathematics

College of Engineering

Systems and Industrial Engineering

College of Science

Mathematics

NonePavlo Krokhmal is currently serving as a Applied Mathematics faculty at University of Arizona.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

Pavlo Krokhmal

University of Arizona

You can click a keyword to filter the displayed items

Notable Scholarly Works

Notable Federal Grants

Collaborators

Comparisons of Unsupervised and Supervised Machine Learning Algorithms for Prediction of Damage in Composites From 3D Micro-Ct Images. (2025)

Reformulation Techniques for Chance-Constrained Combinatorial Optimization Problems. Springer eBooks (2025)

Minimizing the Influence Spread Over a Network Through Node Interception. Optimization Letters (2024)

Shunyu YaoNeng FanPavlo Krokhmal

mathematical optimizationnetwork analysisnode interceptionnetwork optimizationapplied mathematicsinfluence spreadinfluence model

Unsupervised Machine Learning for Automatic Image Segmentation of Impact Damage in Cfrp Composites. Applied Composite Materials (2024)

Olesya ZhupanskaPavlo Krokhmal

Asymptotic Bounds for Clustering Problems in Random Graphs. Networks (2023)

Eugene LykhovydSergiy ButenkoPavlo Krokhmal

network scienceclusteringdata sciencegraph theorynetwork theoryasymptotic bounds

PREFACE: Special Issue of Moa 2020. Journal of Global Optimization (2023)

Ya-Feng LiuZi XuPavlo A. KrokhmalJiming Peng

applied mathematicslarge-scale global optimizationspecial issueoperations researchglobal optimization

Risk‐Averse Optimization and Resilient Network Flows. Networks (2023)

Masoud EshghaliPavlo A. Krokhmal

network scienceresilient network flowssystems engineeringrisk-averse optimization

Stochastic and Risk Averse Maximum Subgraph Problems. Encyclopedia of Optimization (2022)

Masoud EshghaliMaciej RyszPavlo Krokhmal

graph theoryapplied mathematics

Unsupervised Machine Learning Algorithms for Analysis of Low Velocity Impact Damage in Composite Structures From Ct Image Data. (2022)

Olesya I. ZhupanskaPavlo A. Krokhmal

unsupervised machine learningengineeringstructural analysismachine learningmaterials sciencect image dataimage analysiscomputed tomographymechanical engineering

A Scalable Markov Chain Framework for Influence Maximization in Arbitrary Networks. IEEE Transactions on Network Science and Engineering (2021)

Juan S. BorreroMajid AkhgarPavlo A. Krokhmal

network sciencearbitrary networkssystems engineeringinfluence maximization

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computational optimization

discrete math

Stan Uryasev

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finance

stochastic optimization

David Morton

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risk management

Sanjay Mehrotra

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operations research

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network science

network algorithm

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