Faculty

Institution

Unit

Venue

Douglas Nychka

Professor Applied Mathematics and Statistics

Colorado School of Mines

Affiliations

Applied Mathematics & Statistics

Douglas Nychka is currently serving as an Applied Mathematics & Statistics Professor Applied Mathematics and Statistics at Colorado School of Mines.

Honors

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Experiences

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Education

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Douglas Nychka

Colorado School of Mines

Professor Applied Mathematics and Statistics

You can click a keyword to filter the displayed items

statistics data science applied statistics applied mathematics spatial analysis machine learning biostatistics atmospheric science statistical methodology statistical inference meteorology climatology data modeling spatial statistical analysis spatial science nonlinear dynamics geospatial data computational statistics mathematical bioscience regression analysis spatial data bayesian analysis nonlinear science atmospheric research scientific computing chaos theory nonlinear time series high-dimensional chaos spline (mathematics) bibliometrics statistical modeling climate modelling curve fitting estimation theory nonparametric regression markov random fields statistical software nonlinear analysis nonlinear phenomena climatic change earth system science geoscientific model development communicable diseases scientometrics geometric interpolation nonlinear process climate system climate forecasting curve modeling lyapunov analysis spatial theory infectious disease modelling epidemiological dynamic spatial data management large spatial datasets neural networks big spatiotemporal data analytics gaussian process geographic analytics gaussian analysis nonlinear system identification wide area monitoring network monitoring applied meteorology extreme weather bayesian spatial modeling likelihood-based estimation case study competition full gaussian process noisy systems thin plate splines bounded system bayesian confidence intervals numerical model bias multiresolution models climate spectra geographical information science environmental modelling geography applied geography environmental data

Video Presentations

Notable Scholarly Works

Notable Federal Grants

Collaborators

Adapting Quantile Mapping to Bias Correct Solar Radiation Data. Solar Energy (2025)

Maggie D. BaileyDouglas W. NychkaManajit SenguptaJaemo YangYu XieAron HabteSoutir Bandyopadhyay

quantile mappingmachine learningdata sciencebiasstatistics

An Unbiased High-Resolution Climate Dataset for Solar Energy Applications. (2024)

Manajit SenguptaJaemo YangMaggie BaileyAron HabteYu XieDouglas NychkaSoutir Bandyopadhyay

data scienceearth sciencesolar energy applicationsclimatologyenvironmental science

Bias Correction and Statistical Downscaling of Future Solar Irradiance Projections Using the Nsrdb. (2024)

Jaemo YangManajit SenguptaMaggie BaileyDouglas NychkaAron HabteSoutir BandyopadhyayYu Xie

bias correctionbiasstatistical downscalingstatistics

Fast Parameter Estimation of Generalized Extreme Value Distribution Using Neural Networks. Environmetrics (2024)

Sweta RaiAlexis HoffmanSoumendra LahiriDouglas W. NychkaStephan R. SainSoutir Bandyopadhyay

applied mathematicsneural networksmachine learningdata scienceenvironmental science

Normalizing Basis Functions: Approximate Stationary Models for Large Spatial Data. Stat (2024)

Antony SikorskiDaniel McKenzieDouglas Nychka

large spatial datadata scienceapproximate stationary modelsdata normalizationbasis functions

A Gaussian Process Model for Insulin Secretion Reconstruction With Uncertainty Quantification: Applications in Cystic Fibrosis. SIAM Journal on Applied Mathematics (2023)

Justin GarrishChristine ChanDouglas NychkaCecilia Diniz Behn

cystic fibrosispharmacologybiomedical modelingmolecular physiologybiomedical informaticsmathematical sciencesinsulin secretion reconstructionmathematical biosciencebiomedical engineeringmembrane biologyuncertainty quantificationapplied mathematical modellingmathematical biophysicsmathematical biologycomputational medicinecomputational biologyapplied chemistrygaussian process modelapplied mathematics

Regridding Uncertainty for Statistical Downscaling of Solar Radiation. Advances in statistical climatology, meteorology and oceanography (2023)

Maggie D. BaileyDouglas NychkaManajit SenguptaAron HabteYu XieSoutir Bandyopadhyay

oceanographymeteorologystatistical downscalingsolar radiationstatistics

Replication Data for: Functional Forecasting of Dissolved Oxygen in High-Frequency Vertical Lake Profiles. Harvard Dataverse (2023)

Luke DurellJ. Thad ScottDouglas NychkaAmanda S. Hering

aquatic ecosystemsreplication datadata sciencedissolved oxygenfunctional forecastinghydrologyenvironmental scienceecologywater science

Functional Forecasting of Dissolved Oxygen in High‐Frequency Vertical Lake Profiles. Environmetrics (2022)

Luke DurellJ. Thad ScottDouglas NychkaAmanda S. Hering

operational oceanographyaquatic ecosystemswater ecologiesdissolved oxygenlandscape ecologyfunctional forecastinghydrologyenvironmental scienceecologywater science

Adapting Conditional Simulation Using Circulant Embedding for Irregularly Spaced Spatial Data. Stat (2021)

Maggie D. BaileySoutir BandyopadhyayDouglas Nychka

spatial dataspatial analysisgeospatial dataconditional simulationstatistics

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Douglas Nychka

Professor Applied Mathematics and Statistics

Colorado School of Mines

Affiliations

Applied Mathematics & Statistics

Douglas Nychka is currently serving as an Applied Mathematics & Statistics Professor Applied Mathematics and Statistics at Colorado School of Mines.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

Douglas Nychka

Colorado School of Mines

Professor Applied Mathematics and Statistics

You can click a keyword to filter the displayed items

Video Presentations

Notable Scholarly Works

Notable Federal Grants

Collaborators

Adapting Quantile Mapping to Bias Correct Solar Radiation Data. Solar Energy (2025)

Maggie D. BaileyDouglas W. NychkaManajit SenguptaJaemo YangYu XieAron HabteSoutir Bandyopadhyay

quantile mappingmachine learningdata sciencebiasstatistics

An Unbiased High-Resolution Climate Dataset for Solar Energy Applications. (2024)

Manajit SenguptaJaemo YangMaggie BaileyAron HabteYu XieDouglas NychkaSoutir Bandyopadhyay

data scienceearth sciencesolar energy applicationsclimatologyenvironmental science

Bias Correction and Statistical Downscaling of Future Solar Irradiance Projections Using the Nsrdb. (2024)

Jaemo YangManajit SenguptaMaggie BaileyDouglas NychkaAron HabteSoutir BandyopadhyayYu Xie

bias correctionbiasstatistical downscalingstatistics

Fast Parameter Estimation of Generalized Extreme Value Distribution Using Neural Networks. Environmetrics (2024)

Sweta RaiAlexis HoffmanSoumendra LahiriDouglas W. NychkaStephan R. SainSoutir Bandyopadhyay

applied mathematicsneural networksmachine learningdata scienceenvironmental science

Normalizing Basis Functions: Approximate Stationary Models for Large Spatial Data. Stat (2024)

Antony SikorskiDaniel McKenzieDouglas Nychka

large spatial datadata scienceapproximate stationary modelsdata normalizationbasis functions

A Gaussian Process Model for Insulin Secretion Reconstruction With Uncertainty Quantification: Applications in Cystic Fibrosis. SIAM Journal on Applied Mathematics (2023)

Justin GarrishChristine ChanDouglas NychkaCecilia Diniz Behn

Regridding Uncertainty for Statistical Downscaling of Solar Radiation. Advances in statistical climatology, meteorology and oceanography (2023)

Maggie D. BaileyDouglas NychkaManajit SenguptaAron HabteYu XieSoutir Bandyopadhyay

oceanographymeteorologystatistical downscalingsolar radiationstatistics

Replication Data for: Functional Forecasting of Dissolved Oxygen in High-Frequency Vertical Lake Profiles. Harvard Dataverse (2023)

Luke DurellJ. Thad ScottDouglas NychkaAmanda S. Hering

aquatic ecosystemsreplication datadata sciencedissolved oxygenfunctional forecastinghydrologyenvironmental scienceecologywater science

Functional Forecasting of Dissolved Oxygen in High‐Frequency Vertical Lake Profiles. Environmetrics (2022)

Luke DurellJ. Thad ScottDouglas NychkaAmanda S. Hering

operational oceanographyaquatic ecosystemswater ecologiesdissolved oxygenlandscape ecologyfunctional forecastinghydrologyenvironmental scienceecologywater science

Adapting Conditional Simulation Using Circulant Embedding for Irregularly Spaced Spatial Data. Stat (2021)

Maggie D. BaileySoutir BandyopadhyayDouglas Nychka

spatial dataspatial analysisgeospatial dataconditional simulationstatistics

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10 / page

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Similar Faculty Members

Robert Lund

Institution

University of California, Santa Cruz

environmental research

environmental hazard

Jun Yan

Institution

University of Connecticut

statistical software

disaster risk science

Dorit Hammerling

Institution

Colorado School of Mines

remote sensing

geography

Zhengyuan Zhu

Institution

Iowa State University

remote sensing

geography

Michael L. Stein

Institution

University of Chicago

statistics

data science

Dale Zimmerman

Institution

University of Iowa

model analysis

general system

Ronald Gallant

Institution

Pennsylvania State University

statistics

econometrics

Dipak Dey

Institution

University of Connecticut

theoretical biology

biological computation

Rabindra N. Bhattacharya

Institution

University of Arizona

quantitative science study

statistical methodology

Timothy M. DelSole

Institution

George Mason University

atmospheric science

atmospheric chemistry