Video Analytics to Improve Dairy Cattle Health and Welfare

Interdisciplinary Areas: Others

Project Description

Video analytics has the capability of fundamentally changing animal agriculture by providing in real-time analysis of animals and their environment. With video analytics, we can continuously monitor animals while extracting measurements about their behavior and appearance. Quantifying changes in these measurements will allow for increased accuracy in identifying those individual animal or groups of animals that have reduced health or welfare metrics. However, to have advanced video analytic techniques actually adopted within the field of animal agriculture, the video systems need to be robust and accurate even in challenging environments. To date, this has yet to be achieved.

For this project, we are looking to collaborate with a postdoctoral fellow who is interested in the intersection of video analytics and animal science, particularly dairy science, to make a lasting impact in both areas through state-of-the-art video analytic techniques and real-world applications in animal agriculture.


Start Date

January 1, 2024 or later


Postdoc Qualifications

PhD in Electrical and Computer Engineering or a similar field.
We are looking for someone with Python programming skills, with experience working with video files within Python preferred.

Qualities: We are looking for someone who is interested in working with real life video data of animals. We would like someone who is a creative, problem-solver who can understand the broader objectives of the research. They will need to work with a team of faculty and graduate students across colleges, therefore, we are looking for someone who is interested in interdisciplinary research.



Dr. Amy Reibman - Elmore Professor in Electrical and Computer Engineering -

Dr. Jackie Boerman - Associate Professor of Animal Sciences -

Short Bibliography