Mr. Bo Han, Xinjiang Agricultural University, China
Bo Han is a dedicated researcher in the fields of computer science and agricultural informatics, specializing in the application of deep learning for intelligent detection and grading of agricultural products. With a strong foundation in machine learning, data analysis, and big data technology, Bo has successfully led and participated in several research projects aimed at enhancing agricultural processes through artificial intelligence. His current research focuses on the development of intelligent grading systems for apples, with the goal of improving convenience and benefits for fruit farmers. 🌱🍏
Professional Profile:
🎓 Education:
Bo Han is currently pursuing a degree in Agricultural Engineering with a major in Agricultural Information Technology at Xinjiang Agricultural University, Urumqi, China (Sep 2022 – July 2025). He previously earned a degree in Data Science and Big Data Technology from Henan Institute of Science and Technology, Xinxiang, China (Sep 2018 – July 2022). 🎓
💼 Professional Experience:
At Xinjiang Agricultural University, Bo serves as a Structuring Machine Learning Course Assistant, supporting both graduate and undergraduate students in their learning journey (Sep 2023 – Present). 📚
Skills
Bo possesses strong skills in machine learning, data analysis, and big data technologies. His expertise extends to deep learning applications for agricultural product detection and grading. 🤖📊
🏆Awards and Honors
- Provincial First Prize Scholarship 🏆
- Senior Engineer, Artificial Intelligence Trainer
- Certified Data Analyst (Intermediate) 📈
- National College Student Data Analysis Competition (Second Prize)
- China Postgraduate Electronics Competition (Second Prize)
- National College Students Artificial Intelligence Knowledge Contest (First Prize) 🥇
- Outstanding Graduate Students 🌟
Membership
Bo is a member of the China Computer Federation (CCF). 💻
Teaching Experience
Bo is currently assisting in teaching a Structuring Machine Learning course, where he aids in the education of graduate and undergraduate students. 👩🏫👨🏫
Research Focus
Bo’s research focuses on the intelligent grading of apples using deep learning techniques. His projects include the development of hybrid models for apple detection, non-destructive detection of diseased apples, and enhancements in cotton boll detection using advanced YOLO models. He has also worked on various projects related to virtual wheat growth simulation and the prediction of nitrogen application amounts for wheat. 🍎🌾
Publication Top Note:
Rep-ViG-Apple: A CNN-GCN Hybrid Model for Apple Detection in Complex Orchard Environments
Year : 2024
COTTON-YOLO: Enhancing Cotton Boll Detection and Counting in Complex Environmental Conditions Using an Advanced YOLO Model
Year : 2024
Lightweight Non-Destructive Detection of Diseased Apples Based on Structural Re-Parameterization Technique
Year : 2024