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Matthew Walker

Matthew Walker is a Data Scientist who has worked for USGS at the Upper Midwest Environmental Sciences Center since 2023.

Matthew is passionate about data science for social good and applications of computationally intensive statistical methods to research in landscape ecology and anthropology.

Professional Experience

  • Research Data Science Specialist, Translational Data Analytics Institute

  • Research Assistant, Ohio State University

Education and Certifications

  • B.S. Data Analytics, 2021, Ohio State University
    Thesis: A Bayesian Analysis of Landscape Disturbance and the Ecosystem Enhancement of Q'eqchi' Maya Swidden Agriculture

Science and Products

Non-USGS Publications**

Downey, S.S., Walker, M., Moschler, J. et al. An intermediate level of disturbance with customary agricultural practices increases species diversity in Maya community forests in Belize. Commun Earth Environ 4, 428 (2023). https://doi.org/10.1038/s43247-023-01089-6

**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.

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An aerial image of a flock of waterfowl floating on the ocean.

Deep Learning for Automated Detection and Classification of Waterfowl, Seabirds, and other Wildlife from Digital Aerial Imagery

The U.S. Geological Survey Upper Midwest Environmental Sciences Center is developing deep learning algorithms and tools for the automatic detection, enumeration, classification, and annotation of seabirds and other marine wildlife from digital aerial imagery — advancing cutting-edge research in collaboration with the Bureau of Ocean Energy Management (BOEM), the U.S. Fish and Wildlife Service (FWS...
By
Ecosystems Mission Area, Species Management Research Program, Upper Midwest Environmental Sciences Center
link

Deep Learning for Automated Detection and Classification of Waterfowl, Seabirds, and other Wildlife from Digital Aerial Imagery

The U.S. Geological Survey Upper Midwest Environmental Sciences Center is developing deep learning algorithms and tools for the automatic detection, enumeration, classification, and annotation of seabirds and other marine wildlife from digital aerial imagery — advancing cutting-edge research in collaboration with the Bureau of Ocean Energy Management (BOEM), the U.S. Fish and Wildlife Service (FWS...
Learn More

Science and Products

Non-USGS Publications**

Downey, S.S., Walker, M., Moschler, J. et al. An intermediate level of disturbance with customary agricultural practices increases species diversity in Maya community forests in Belize. Commun Earth Environ 4, 428 (2023). https://doi.org/10.1038/s43247-023-01089-6

**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.

link
An aerial image of a flock of waterfowl floating on the ocean.

Deep Learning for Automated Detection and Classification of Waterfowl, Seabirds, and other Wildlife from Digital Aerial Imagery

The U.S. Geological Survey Upper Midwest Environmental Sciences Center is developing deep learning algorithms and tools for the automatic detection, enumeration, classification, and annotation of seabirds and other marine wildlife from digital aerial imagery — advancing cutting-edge research in collaboration with the Bureau of Ocean Energy Management (BOEM), the U.S. Fish and Wildlife Service (FWS...
By
Ecosystems Mission Area, Species Management Research Program, Upper Midwest Environmental Sciences Center
link

Deep Learning for Automated Detection and Classification of Waterfowl, Seabirds, and other Wildlife from Digital Aerial Imagery

The U.S. Geological Survey Upper Midwest Environmental Sciences Center is developing deep learning algorithms and tools for the automatic detection, enumeration, classification, and annotation of seabirds and other marine wildlife from digital aerial imagery — advancing cutting-edge research in collaboration with the Bureau of Ocean Energy Management (BOEM), the U.S. Fish and Wildlife Service (FWS...
Learn More
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