UGA Athens Campus
Office: 1311 Miller Plant Sciences
Dr. Zhihang Song is a dedicated agricultural researcher 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 crop production.
Dr. Song’s Ph.D. research centered on developing innovative methods to identify nutrient deficiencies in crops, using high-resolution leaf images interpreted through explainable machine-learning models. His approach has been successfully applied to detect nitrogen deficiencies in corn and soybean, providing real-time diagnostic tools for farmers and stakeholders.
With a strong interdisciplinary background spanning crop mineral nutrient analysis, sensor development, and controlled environment farming, Dr. Song is creating sustainable agricultural practices through data-driven insights. His research efforts, including engagement with local growers through USDA NRCS projects, have enriched his understanding of practical farming challenges.
Dr. Song is also passionate about mentoring the next generation of scientists, having been recognized with the Estus H. and Vashti L. Magoon Award for Excellence in Teaching during his time as a Teaching Assistant. As an active participant in community-focused initiatives, such as the Wabash Heartland Innovation Network, he looks forward to contributing his expertise to UGA’s mission and to support agricultural sustainability and efficiency.
Appointments
- 70% Research
- 25% Instruction
- 5% Service
Teaching
- Coming soon
Education
- B.S. in Agricultural Engineering, China Agricultural University (CAU), Beijing, China, 2017
- B.S. in Agricultural Engineering (Machine Systems) Purdue University, West Lafayette, IN, 2017
- M.S. in Agricultural & Biological Engineering, Purdue University, West Lafayette, IN, 2020
- Ph.D. in Agricultural & Biological Engineering, Purdue University, West Lafayette, IN, 2024