Faculty

Institution

Unit

Venue

Kevin Lin

University of Arizona

Affiliations

Mathematics

Applied Mathematics

College of Science

Mathematics

NoneKevin Lin 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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Kevin Lin

University of Arizona

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applied mathematics neuroscience dynamical systems nonlinear dynamics computational neuroscience nonlinear science cognitive neuroscience chaos theory systems neuroscience nonlinear phenomena physics oscillation theory nonlinear oscillations neural computation neural circuits brain modeling systems biology theoretical biology neurodynamics reliability scientific computing nonlinear analysis bayesian analysis mathematical physics developmental cognitive neuroscience brain circuitry neuronal networks brain mapping mathematical bioscience statistical physics neural mechanisms network dynamics dynamic networks brain function hamiltonian system brain science coupled oscillators reliability engineering bio-inspired computation nonlinear process temporal networks applied mathematical modelling markov chain monte carlo perturbation methods stochastic calculus nonequilibrium steady states kuramoto-sivashinsky equation wiener projections neural oscillator models temporal drive quantum resonances robust nonlinear control scientometrics localization medical image computing nonlinear control chaotic mixing random graphs spatio-temporal models brain organization cellular neurobiology molecular neurobiology mathematical biophysics integrable systems biological networks coalition formation biomedical technologies data-driven model reduction koopman-mori-zwanzig formalism phase-amplitude descriptions shear-induced chaos chaotic scattering random itineraries spatial scale grid-to-place cell model dorsoventral axis computational mathematics quantum biology mathematical biology mathematics

Notable Scholarly Works

Notable Federal Grants

Collaborators

Detection of Latent Brain States From Baseline Neural Activity in the Amygdala. bioRxiv (Cold Spring Harbor Laboratory) (2024)

Alexa AucoinKevin K. LinKatalin M. Gothard

cognitive neurosciencebrain scienceneural circuitsneuroimaginglatent brain statesbaseline neural activitysystems neurosciencebrain functionneuroscience

Efficient Models of Cortical Activity via Local Dynamic Equilibria and Coarse-Grained Interactions. Proceedings of the National Academy of Sciences (2024)

Zhuo-Cheng XiaoKevin K. LinLai-Sang Young

cognitive neurosciencelocal dynamic equilibriascientometricscortical activitycomputational neurosciencesystems neuroscienceneurodynamicsbrain modelingcognitive sciencecoarse-grained interactionsefficient modelsneuroscience

A Comparison of Probe Geometries for Neuronal Localization. 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (2022)

Patrick GreeneKevin K. Lin

biomedical engineeringbiomedical technologiesneuronal localizationprobe geometriesneural engineering

Multilevel Monte Carlo for Cortical Circuit Models. Journal of Computational Neuroscience (2022)

Zhuo-Cheng XiaoKevin K. Lin

multilevel monte carlocomputational neuroscienceneurosciencecortical circuit models

A Data-Informed Mean-Field Approach to Mapping of Cortical Parameter Landscapes. PLoS Computational Biology (2021)

Zhuo-Cheng XiaoKevin K. LinLai-Sang Young

cognitive neurosciencecomputational neurosciencecortical parameter landscapessystems neurosciencestatisticsdata sciencebrain mappingneuroscience

Conjunctive Reward–Place Coding Properties of Dorsal Distal Ca1 Hippocampus Cells. Biological Cybernetics (2020)

Zhuocheng XiaoKevin LinJean-Marc Fellous

cognitive neurosciencemolecular neurosciencebrain organizationmolecular neurobiologysystems neurosciencecentral nervous systembrain functioncognitive sciencecellular neurobiologyneuroscienceneuroanatomycell biology

Data-Driven Model Reduction, Wiener Projections, and the Koopman-Mori-Zwanzig Formalism. Journal of Computational Physics (2020)

Kevin K. LinFei Lu

scientific computingwiener projectionsmachine learningkoopman-mori-zwanzig formalismdata-driven model reductionformal methodsdata sciencecomputer science

Symmetrized Importance Samplers for Stochastic Differential Equations. Communications in Applied Mathematics and Computational Science (2018)

Andrew LeachKevin LinMatthias Morzfeld

scientific computingstochastic calculusstochastic processimportance samplersapplied mathematicsstochastic differential equations

Comparison of Continuous and Discrete-Time Data-Based Modeling for Hypoelliptic Systems. Communications in Applied Mathematics and Computational Science (2016)

Fei LuKevin LinAlexandre Chorin

scientific computingdata modelinghypoelliptic systemssystems modelingmodeling and simulationapplied mathematicsapplied physicscomputer scienceapplied mathematical modellingdiscrete-time data-based modeling

Data-Based Stochastic Model Reduction for the Kuramoto–Sivashinsky Equation. Physica D Nonlinear Phenomena (2016)

Fei LuKevin K. LinAlexandre J. Chorin

physicsparticle physicsmathematical physicskuramoto-sivashinsky equationapplied mathematicsapplied physics

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Kevin Lin

University of Arizona

Affiliations

Mathematics

Applied Mathematics

College of Science

Mathematics

NoneKevin Lin 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

Kevin Lin

University of Arizona

You can click a keyword to filter the displayed items

Notable Scholarly Works

Notable Federal Grants

Collaborators

Detection of Latent Brain States From Baseline Neural Activity in the Amygdala. bioRxiv (Cold Spring Harbor Laboratory) (2024)

Alexa AucoinKevin K. LinKatalin M. Gothard

cognitive neurosciencebrain scienceneural circuitsneuroimaginglatent brain statesbaseline neural activitysystems neurosciencebrain functionneuroscience

Efficient Models of Cortical Activity via Local Dynamic Equilibria and Coarse-Grained Interactions. Proceedings of the National Academy of Sciences (2024)

Zhuo-Cheng XiaoKevin K. LinLai-Sang Young

A Comparison of Probe Geometries for Neuronal Localization. 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (2022)

Patrick GreeneKevin K. Lin

biomedical engineeringbiomedical technologiesneuronal localizationprobe geometriesneural engineering

Multilevel Monte Carlo for Cortical Circuit Models. Journal of Computational Neuroscience (2022)

Zhuo-Cheng XiaoKevin K. Lin

multilevel monte carlocomputational neuroscienceneurosciencecortical circuit models

A Data-Informed Mean-Field Approach to Mapping of Cortical Parameter Landscapes. PLoS Computational Biology (2021)

Zhuo-Cheng XiaoKevin K. LinLai-Sang Young

cognitive neurosciencecomputational neurosciencecortical parameter landscapessystems neurosciencestatisticsdata sciencebrain mappingneuroscience

Conjunctive Reward–Place Coding Properties of Dorsal Distal Ca1 Hippocampus Cells. Biological Cybernetics (2020)

Zhuocheng XiaoKevin LinJean-Marc Fellous

Data-Driven Model Reduction, Wiener Projections, and the Koopman-Mori-Zwanzig Formalism. Journal of Computational Physics (2020)

Kevin K. LinFei Lu

scientific computingwiener projectionsmachine learningkoopman-mori-zwanzig formalismdata-driven model reductionformal methodsdata sciencecomputer science

Symmetrized Importance Samplers for Stochastic Differential Equations. Communications in Applied Mathematics and Computational Science (2018)

Andrew LeachKevin LinMatthias Morzfeld

scientific computingstochastic calculusstochastic processimportance samplersapplied mathematicsstochastic differential equations

Comparison of Continuous and Discrete-Time Data-Based Modeling for Hypoelliptic Systems. Communications in Applied Mathematics and Computational Science (2016)

Fei LuKevin LinAlexandre Chorin

Data-Based Stochastic Model Reduction for the Kuramoto–Sivashinsky Equation. Physica D Nonlinear Phenomena (2016)

Fei LuKevin K. LinAlexandre J. Chorin

physicsparticle physicsmathematical physicskuramoto-sivashinsky equationapplied mathematicsapplied physics

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dynamical systems

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David Cai

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stochastic process

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quantitative science study

statistical methodology

Edward C. Waymire

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anomalous diffusion

heterogeneous porous media

Chris Tsokos

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ecological modelling