Investigating the Link Between Personality and Problem-Solving in Captive Gray Wolves

Graduate student: Yasmeen Ghavamian

Date: 2022-present

Goals: To evaluate the personality of captive gray wolves living in packs and assess individual differences in problem-solving strategies to understand how an individual’s personality may predict their ability to cope with changes in their environment.


Lojacked Bovine

Personality Traits in Beef Cattle and how they Relate to Grazing Distribution on Extensive Rangelands

Graduate Student: Maggie Creamer

Date: 2019 – Present


  1. Identify reliable multidimensional personality traits in beef cattle across several contexts
  2. Relate personality measures to foraging patterns and movement via GPS data


Creamer, M., & Horback, K. (2021). Researching human-cattle interaction on rangelands: challenges and potential solutions. Animals11(3), 725.

Creamer, M. L., Roche, L. M., Horback, K. M., & Saitone, T. L. (2020). Optimising cattle grazing distribution on rangeland: a systematic review and network analysis. The Rangeland Journal41(5), 441-455.


Investigation of Consistent Individual Differences During Pre- and Post-Natal, Human-Animal Interactions in Rangeland Ewes.


Graduate student: Kaleiah Schiller

Date: 2019 – present

Goals: Assess consistency of behavioral responses towards a human stimulus during and outside of the lambing season to understand context specificity or domain generality of phenotypic traits in rangeland ewes.



Schiller, K., McVey, C., Doyle, S., & Horback, K. (2020). Chute scoring as a potential method for assessing individual differences in arousal among ewes. Applied Animal Behaviour Science230, 105073.


Livestock Informatics Toolkit (LIT)

Graduate Student: Catie McVey

Date: 2019 – 2022


  1. Developing Unsupervised Machine Learning (UML) algorithms to visualize and quantify complex behavioral patterns.
  2. Using Information Theoretic Approaches to reveal the complex relationships between performance on controlled behavioral assays, home pen behaviors recorded by precision manage-met tools, and outcome measures such as health and productivity.

Open Source Code:

McVey C, Hsieh F, Manriquez D, Pinedo P and Horback K (2020) Mind the Queue: A Case Study in Visualizing Heterogeneous Behavioral Patterns in Livestock Sensor Data Using Unsupervised Machine Learning Techniques. Front. Vet. Sci. 7:523. doi: 10.3389/fvets.2020.00523

McVey, C., Hsieh, F., Manriquez, D., Pinedo, P., & Horback, K. (2022). Livestock Informatics Toolkit: A Case Study in Visually Characterizing Complex Behavioral Patterns across Multiple Sensor Platforms, Using Novel Unsupervised Machine Learning and Information Theoretic Approaches. Sensors22(1), 1.

McVey, C., Hsieh, F., Manriquez, D., Pinedo, P., & Horback, K. (2023). Invited Review: Applications of unsupervised machine learning in livestock behavior: Case studies in recovering unanticipated behavioral patterns from precision livestock farming data streams. Applied Animal Science39(2), 99-116.

Facial Inference Toolkit (FIT)

Graduate Student: Catie McVey

Date: 2019 – 2022


  1. Develop algorithmic tools (projective biometrics) to quantify facial structure in livestock
  2. Developing algorithmic tools to correct for the impact of camera angle on measurements from 2D images of minimally restrained livestock
  3. Developing algorithmic tools to quantify facial expressions in livestock


McVey, C., Egger, D., & Pinedo, P. (2022). Improving the Reliability of Scale-Free Image Morphometrics in Applications with Minimally Restrained Livestock Using Projective Geometry and Unsupervised Machine Learning. Sensors22(21), 8347.

Effect of rearing environment on the development of depth perception in egg-laying hens

Graduate Student: Claire Jones

Date: 2019 – 2021

Goals: Assess depth perception in egg laying hens using a Y-maze task and visual cliff apparatus.


Jones, C. T., Pullin, A. N., Blatchford, R. A., Makagon, M. M., & Horback, K. (2023). Effects of rearing with vertical structures on the ontogeny of depth perception in laying hens. Applied Animal Behaviour Science, 105837.