Mr. Bo Han | Agri-Tech Apps | Best Scholar Award

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:

Orcid

🎓 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

Mr. Wei Fan | Agri-Tech Apps Awards | Best Researcher Award

Mr. Wei Fan, Inner Mongolia University, China

Mr. Wei Fan is currently pursuing a Ph.D. in Electronic Information at Inner Mongolia University, building on his solid academic foundation with a B.S. in Measurement and Control Technology from Inner Mongolia University of Science and Technology. His research focuses on enhancing LIDAR-based SLAM for robotics by integrating dynamic object removal capabilities. Mr. Fan has demonstrated exceptional leadership as a Student Leader and Learning Committee Member, contributing to class management, academic supervision, and event planning. His dedication to innovation is underscored by his achievements, including winning the Gold Award at the China International “Internet+” Innovation and Entrepreneurship Competition and the Provincial First Prize in the “Zhao Yi Cup” Chinese Graduate Electronic Design Competition.

🎓 Education:

Ph.D. in Electronic Information
Inner Mongolia University, China (09.2022 – Present)

B.S. in Measurement and Control Technology
Inner Mongolia University of Science and Technology, China (09.2018 – 07.2022)

Key Courses: Intelligent Control, Random Signals, Circuit Design, Fuzzy Control, Matrix Theory, etc.

🌱 Campus Projects:

Graduate Research Project on Dynamic Environment Robust Fast LIDAR Odometry and Mapping
Focuses on integrating dynamic object removal capabilities into LIDAR-based SLAM for enhanced accuracy in robotics.

National Key R&D Project on Eco-management of Grassland Livestock Balance
Uses integrated sky-ground technology for tracking and behavior recognition of livestock, predicting grass growth models, and implementing precision grazing using deep learning techniques.