Zhihang Song
Assistant Professor; Emphasis: Plant Phenomics, Controlled Environment Agriculture
Areas of expertise
About
Dr. Zhihang Song is an Assistant Professor of Controlled Environment Agriculture (CEA) Phenomics in the Department of Horticulture with a focus on advancing digital agriculture to enhance food security and sustainability. His work integrates technologies such as imagery sensors, machine learning, computer vision, and robotics to tackle critical challenges in specialty crop breeding and crop condition monitoring in CEA. Dr. Song is also passionate about mentoring the next generation of scientists, engineers, and scholars ready to contribute to the agricultural industry and academia.
Education
Doctor of Philosophy, Agricultural Engineering.
Purdue University, IN, United States (2024)
Master of Science, Agricultural Engineering.
Purdue University, IN, United States (2020)
Bachelor of Science, Agricultural Engineering.
Purdue University, IN, United States (2017)
Courses
- HORT 8160: Measurement and Control in Plant and Soil Science (Fall 2025)
- HORT 7000: Master's Research (Fall 2025)
- HORT 7000: Master's Research (Spring 2026)
- HORT 9000: Doctoral Research (Spring 2026)
- HORT 7000: Master's Research (Summer 2026)
- HORT 9000: Doctoral Research (Summer 2026)
- HORT 9000: Doctoral Research (Fall 2026)
- HORT 4710: Plant Phenotyping Technologies (Fall 2026)
- HORT 6710: Plant Phenotyping Technologies (Fall 2026)
- HORT 7000: Master's Research (Fall 2026)
Scholarly Works
- Controlled Environment Agriculture Basics: Changing the Way We Grow, (2026).
- Development and Validation of Internet of Things-Enabled Weighing System for Cage-Free Poultry Houses, SENSORS, (2026).
- Hyperspectral image-based leaf-level spatial and spectral feature mining for phosphorus deficiency symptom differentiation in corn plants at early vegetative stage, COMPUTERS AND ELECTRONICS IN AGRICULTURE, (2026).
- PhenoBee: Drone-based robot for advanced field in vivo contact-based phenotyping in agriculture, COMPUTERS AND ELECTRONICS IN AGRICULTURE, (2025).
- A high-precision spatial and spectral imaging solution for accurate corn nitrogen content level prediction at early vegetative growth stages, COMPUTERS AND ELECTRONICS IN AGRICULTURE, (2025).
Contact
Mailing Address
1111 Plant Sciences Building
Athens, GA 30602
Shipping Address
1111 Plant Sciences Building
Athens, GA 30602
Own this profile? Learn how to make changes


