Travis Harrison
Develops web applications and statistical software for the management and analysis of scientific data.
Biography
Education:
- B.S. Statistics, University of Wisconsin - La Crosse, La Crosse, WI, 2017
Research Interests:
- Web applications and statistical software
- Data management and summarization
- Statistics and machine learning
Current Projects:
- Deep learning for automated detection and classification of waterfowl, seabirds, and other marine wildlife from digital aerial imagery
- Web applications for the management, visualization and analysis of fish catch and telemetry data
Science and Products
Database and web application for invasive carp catch data (Illinois River Catch Database)
Four types of invasive carp are currently found in the United States: black, grass, silver, and bighead carps. These species are fast growing, prolific feeders that out-compete native fish species and drastically alter the natural ecosystems they invade. To prevent the spread of invasive carp into the Great Lakes, the multi-agency Asian Carp Regional...
Database and web application for invasive carp telemetry data (FishTracks)
Four types of invasive carp fish species, are currently found in the United States: black, grass, silver, and bighead carps. These species are fast growing, prolific feeders that out-compete native fish species and drastically alter the natural ecosystems they invade. To prevent the spread of invasive carp into the Great Lakes, the multi-agency Asian Carp...
USGS Cloud Environment Cookbook
The cloud offers new and exciting opportunities for USGS employees to leverage computing resources and services that can quickly improve their workflows and reduce expenditures typically associated with establishing a comparable environment with physical infrastructure. However, due to the novelty of access to and use of the cloud environment, there is limited documentation and shared examples...
Deep Learning for Automated Detection and Classification of Waterfowl, Seabirds, and other Wildlife from Digital Aerial Imagery
In collaboration with the Bureau of Ocean Energy Management, U.S. Fish and Wildlife Service, and the Vision Group at the International Computer Science Institute at the University of California - Berkeley, the U.S. Geological Survey Upper Midwest Environmental Sciences Center is developing deep learning algorithms and tools for the automatic detection, enumeration, classification, and...
Patterns of mercury and selenium exposure in Minnesota common loons
Common loons (Gavia immer) are at risk of elevated dietary mercury (Hg) exposure in portions of their breeding range. To assess the level of risk among loons in Minnesota (USA), we investigated loon blood Hg concentrations in breeding lakes across Minnesota. Loon blood Hg concentrations were regressed on predicted Hg concentrations in standardized...
Kenow, Kevin P.; Houdek, Steven C.; Fara, Luke J.; Erickson, Richard A.; Gray, Brian R.; Harrison, Travis J.; Monson, Bruce; Henderson, Carrol L.