Chun-Peng James Chen

Assistant Professor of Animal Data Sciences

Virginia Tech

United States

Research Interests

Explore related searches

Professors in United States

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

About

Chun-Peng James Chen is an Assistant Professor of Animal Data Sciences at Virginia Tech, USA. His research focuses on animal data analysis and machine learning applications in agriculture, with recent publications covering topics such as ant behavior analysis, model generalization in livestock detection, and nutritional value assessment of forages. Additionally, he addresses methodologies for evaluating animal activity data and genetic studies in dairy cattle.

Articles (11)

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2023

Year:

2023

Year:

2022

Year:

2022

Year:

2022

Year:

2020

Year:

2020

Collaborators (6)

Zhiwu Zhang

Professor

Washington State University

UNITED STATES

View details

Camille M Steber

Washington State University

UNITED STATES

View details

Arron H. Carter

UNITED STATES

View details

Rohan Fernando

Professor Emeritus of Animal Science

Iowa State University

UNITED STATES

View details

Kiho Lee

Associate Professor

University of Missouri

UNITED STATES

View details

Emre Karaman

Associate Professor

Aarhus University

DENMARK

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Chun-Peng James Chen

Research Interests

Explore related searches

Contact this professor

About

Articles (11)

An automated approach for counting ants in densely populated images and gaining insight into ant foraging behavior

Evaluating model generalization for cow detection in free-stall barn settings: Insights from the COw LOcalization (COLO) dataset

Common pitfalls in evaluating model performance and strategies for avoidance in agricultural studies

Spectral sensing for forage nutritive value determination of cool season, grass pastures during the grazing season

Evaluation of walking activity data during pregnancy as an indicator of pregnancy loss in dairy cattle

An independent validation reveals the potential to predict Hagberg–Perten falling number using spectrometers

VTag: a semi-supervised pipeline for tracking pig activity with a single top-view camera

As the number falls, alternatives to the Hagberg–Perten falling number method: A review

XSim version 2: simulation of modern breeding programs

GWAS-Based Identification of New Loci for Milk Yield, Fat, and Protein in Holstein Cattle

GRID: A Python Package for Field Plot Phenotyping Using Aerial Images

Collaborators (6)

Zhiwu Zhang

Camille M Steber

Arron H. Carter

Rohan Fernando

Kiho Lee

Emre Karaman

Make your next move.