Brian Hutchinson

Associate Professor

Western Washington University

United States

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Brian Hutchinson is an Associate Professor at Western Washington University in the United States. His research focuses on data-driven astrophysics, machine learning applications in environmental science, and forecasting methodologies. Recent works include advancements in the analysis of variable stars, the development of spectroscopic parameters for diverse stellar populations, and innovative approaches to energy consumption forecasting in built environments.

Articles (12)

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2025

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2025

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2024

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2024

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2024

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2023

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2022

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2021

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2020

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2020

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2020

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2020

Collaborators (3)

Kevin Covey

Associate Professor

Western Washington University

UNITED STATES

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Marina Kounkel

Assistant Professor

University of North Florida

UNITED STATES

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Ben Kravitz

Assistant Professor

Indiana State University

UNITED STATES

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Brian Hutchinson

Research Interests

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Articles (12)

A Spatiotemporal Data Cube Approach to Classification of Variable Stars: A Catalog of Candidate Variable Stars from the TESS Full-frame Image Raw Data

Gaia Net: Toward Robust Spectroscopic Parameters of Stars of all Evolutionary Stages

DiffESM: Conditional Emulation of Temperature and Precipitation in Earth System Models With 3D Diffusion Models

A Self-consistent Data-driven Model for Determining Stellar Parameters from Optical and Near-infrared Spectra

Use of machine learning to analyze chemistry card sort tasks

Dilated causal convolutional neural networks for forecasting zone airflow to estimate short-term energy consumption

APOGEE Net: An Expanded Spectral Model of Both Low-mass and High-mass Stars

Untangling the Galaxy. III. Photometric Search for Pre-main-sequence Stars with Deep Learning

SWRL Net: A Spectral, Residual Deep Learning Model for Improving Short-Term Wave Forecasts

Sequence-to-sequence neural networks for short-term electrical load forecasting in commercial office buildings

APOGEE Net: Improving the Derived Spectral Parameters for Young Stars through Deep Learning

Technical note: Deep learning for creating surrogate models of precipitation in Earth system models

Collaborators (3)

Kevin Covey

Marina Kounkel

Ben Kravitz

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