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MDPI’s Journal Cluster of Animal Science Webinar | Artificial Intelligence and Digital Technologies for Animal Health and Sustainable Management

11 November 2026
14:00 (CET)
Online

Welcome from
the chair

MDPI’s Journal Cluster of Animal Science Webinar 

Artificial Intelligence and Digital Technologies for Animal Health and Sustainable Management

In this webinar, we would like to explore recent advances and emerging trends in artificial intelligence and digital technologies for animal health and sustainable management. Our speakers will share insights into innovative approaches to improving animal health, welfare, and sustainable livestock production. We warmly invite you to join us, engage with our expert presenters, and discuss the opportunities and challenges of applying these technologies in animal science.

Date: 11 November 2026
Time: 14:00 CET | 08:00 EST 
Webinar ID: Webinar ID859 4135 5617
Webinar Secretariat: journal.webinar@mdpi.com



Meet Our Chair

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Prof. Andrea Pezzuolo

University of Padova, Italy;

Meet Our Speakers

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Dr. Shu Hang

China Agricultural University, China;Shu Hang, Ph.D. in Agricultural Science and Bioengineering, is an Associate Professor in the Department of Intelligent Animal Production and Environmental Science, College of Animal Science and Technology, China Agricultural University. His research focuses on intelligent animal information monitoring and the comprehensive evaluation of livestock housing environments. He has published 20 peer-reviewed papers in journals including Computers and Electronics in Agriculture, Biosystems Engineering and Animals, and co-authored two book chapters.

Dr. Isabella Condotta

University of Illinois Urbana-Champaign, USA;Isabella Condotta is an Assistant Professor in the Department of Animal Sciences at the University of Illinois Urbana-Champaign, where she leads the Illinois Digital Animal Systems Lab (I-DigitAL). Her research develops and evaluates precision animal management technologies using artificial intelligence, computer vision, audio, and wearable sensing to monitor animal behavior, health, welfare, reproduction, body condition, and performance. Her work spans multiple livestock species and emphasizes the development and validation of practical sensing and decision-support tools for both housed and grazing systems.

Dr. Lilong  Chai

University of Georgia, USA;Dr. Lilong Chai is an Associate Professor and Engineering Specialist in the Department of Poultry Science at the University of Georgia (UGA). He is a UGA Aspire Fellow and Steering Committee Member of the UGA Institute for Integrative Precision Agriculture. Chai’s research and extension interests include sustainable animal production, precision poultry farming, and poultry health and welfare. Chai is author/coauthor of 300 scientific publications (including 100 journal articles, 150 conference papers/abstracts, and 60 extension articles) and PI/Co-PI on 40 grants/contracts. He is currently the Coordinator of Georgia Precision Poultry Farming Conference and Georgia Layer Conference, two annual extension poultry training programs at UGA; the Chair of 4th U.S. Precision Livestock Farming Conference (2025-2027); and a Section Editor of the Poultry Science and Scientific Reports journals. Chai’s research and extension efforts have been recognized with 20 professional awards and honors, including 2025 American Egg Board Research Award and 2021 ASABE Sunkist Young Designer Award.

Dr. Anderson Alves

University of Georgia, USA;Anderson A. C. Alves, PhD, is an Assistant Professor in the Department of Animal and Dairy Science at the University of Georgia–Athens. Dr. Alves earned his PhD in Animal Breeding and Genetics from São Paulo State University, Brazil, in 2019, followed by a postdoctoral training in Precision Livestock Farming and Data Analytics at the University of Wisconsin-Madison (2021-2023). Dr. Alves’ research focuses on the development and application of statistical learning methods and computational tools for high-dimensional livestock data analysis. His work integrates statistical modeling, machine learning, computer vision, and on-farm sensor technologies to monitor animal health, welfare, and productivity, supporting efficient, data-driven livestock management. His group also investigates the genetic architecture of novel and hard-to-measure quantitative traits generated by digital technologies and algorithms to improve economically and socially important indicators in livestock production systems. He has authored or co-authored over 90 publications spanning data analytics, quantitative genetics, machine learning, computer vision, and mixed linear models applied to livestock systems.

Prof. Patrícia Ferreira Ponciano Ferraz

Federal University of Lavras (UFLA), Brazil;Patrícia Ferreira Ponciano Ferraz is an Associate Professor in the Department of Agricultural Engineering and a permanent faculty member of the Graduate Program in Agricultural Engineering at the Federal University of Lavras (UFLA), Brazil. She holds a Bachelor's degree in Animal Science and both a Master's and a Ph.D. in Agricultural Engineering, specializing in Rural Buildings and Animal Environment, from UFLA. Her international academic experience includes appointments as a Visiting Professor at Universidad Nacional de Colombia (Colombia, 2017), a postdoctoral researcher at the University of Florence (Italy, 2020), and a Visiting Researcher at KU Leuven (Belgium, 2023) and Florida International University (USA, 2026). She is a Research Productivity Fellow of the Brazilian National Council for Scientific and Technological Development (CNPq) and coordinates the Center for Research in Intelligent Agriculture and Livestock (CEAPI), as well as funded projects and national and international research networks. Her research focuses on Precision Livestock Farming, digital technologies, animal welfare, and artificial intelligence applied to livestock production systems. She has published 114 peer-reviewed journal articles and 207 conference papers.

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