Xin (Rex) Sun

Endowed Chair and Director of the Peltier Institute, Associate Professor

Faculty

Agricultural and Biosystems Engineering

Dr. Rex Sun

Dr. Xin (Rex) Sun is an Associate Professor in Agricultural and Biosystems Engineering and serves as the inaugural Endowed Chair and Director of the Peltier Institute for Advancement in Agricultural Technology at North Dakota State University. Dr. Sun’s research leverages artificial intelligence, field robotics, and remote sensing to transform data-driven decision-making in agriculture. His work focuses on developing autonomous systems for weed detection, soil health assessment, and crop monitoring. With over $23 million in competitive research funding and more than $5 million as Principal Investigator, he leads interdisciplinary teams that bridge cutting-edge science with real-world applications.

Areas of Study & Research

  • Precision Agriculture Technologies
  • Field Robotics & Automation
  • Artificial Intelligence & Machine Learning
  • Hyperspectral & Multispectral Imaging
  • Data-Driven Decision Support
  • Technology Transfer & Grower Engagement

Other Research Interests

  • Edge-AI deployment for low-connectivity agricultural environments
  • Data fusion from multi-sensor platforms for enhanced decision-making
  • Human–robot interaction in field-based agricultural systems
  • Resilient agtech solutions for tribal and underserved farming communities
  • Interdisciplinary approaches to ag education and workforce development

Courses Taught

  • PAG 115 – Introduction to Precision Agriculture
  • PAG 115L – Precision Agriculture Laboratory
  • PAG 215 – Mapping of Precision Ag Data
  • PAG 315 – Electronic Systems in Precision Agriculture
  • PAG 496 – Field Experience / Practicum

Previous Work

Before joining the faculty at North Dakota State University, Dr. Xin (Rex) Sun served as a Research Scientist in the Department of Animal Sciences at NDSU, where he focus on projects of meat quality evaluation and Precision Livestock Production research using imaging and AI technologies.

Current Grants

  • Developing systems to expedite phenotyping of biotic and abiotic stress tolerance in Brassica oilseed and small grain cereal crops
  • Identification of Sudden Death Syndrome in Soybean using hyperspectral imaging and deep learning technologies
  • Intelligence on-farm weed control solution based on Edge-AI and UGV systems
  • Fusion of machine learning and electromagnetic sensors for real-time local decisions in agriculture
  • Dynamic, data-driven, sustainable, and resilient crop production systems for the U.S.
  • Uncrewed Autonomous Systems (UAS) student scholarship

Awards & Honors

  1. 2024 NDSU Agriculture and Extension Faculty/Staff Award: Larson/Yaggie Excellence in Research Award
  2. 2023 NDSU College of Engineering Early Researcher Award

Professional Associations

American Society of Agricultural and Biological Engineers (ASABE)

Institute of Electrical and Electronics Engineers (IEEE)

Links

University Affiliations

Agricultural and Biosystems Engineering

Education

  • Nanjing Agricultural University 2013
  • Yantai University 2007

Publications

  1. Villamil-Mahecha, M., Pathak, H., Rai, N., Overby, P., & Sun, X*. (2025). Deep learning for sunflower (Helianthus annuus L.) mapping and stand counting: Trade-offs between closed vs. open-access methods. Smart Agricultural Technology, 101235.
  2. Pa Tamba Jammeh, Brent Hulke, Jarrad Prasifka, Xin Sun, & Ewumbua Monono. (2025). Aerodynamics Properties of Silflower Seed: Effect of Moisture and Seed Morphology. Journal of the ASABE.
  3. Upadhyay, A., Sunil, G. C., Das, S., Mettler, J., Howatt, K., & Sun, X*. (2025). Multiclass weed and crop detection using optimized YOLO models on edge devices. Journal of Agriculture and Food Research, 102144.
  4. Mensah, B., Prasifka, J., Hulke, B., Monono, E., & Sun, X*. (2025). Detection of insect-damaged sunflower seeds using near-infrared hyperspectral imaging and machine learning. Smart Agricultural Technology, 101110.
  5. Wiafe, E. K., Betitame, K., Ram, B. G., & Sun, X*. (2025). Technical study on the efficiency and models of weed control methods using unmanned ground vehicles: A review. Artificial Intelligence in Agriculture.
  6. Huang, Y., Sun, X., Rai, N., Yao, H., Reddy, K. N., & Jenkins, J. (2025). Remote sensing for precision weed management. Pest Management Science.
  7. Zhang, X., Sun, X., & Lin, Z. (2025). Improving Soil Moisture Prediction Using Gaussian Process Regression. Smart Agricultural Technology, 100905.
  8. Upadhyay, A., Sunil, G. C., Mahecha, M. V., Mettler, J., Howatt, K., Aderholdt, W., Ostlie, M., & Sun, X*. (2025). Weed-crop dataset in precision agriculture: Resource for AI-based robotic weed control systems. Data in Brief. 111486.
  9. Betitame, K., Igathinathane, C., Howatt, K., Mettler, J., Koparan, C., & Sun, X*. (2025). A Practical Guide to UAV-Based Weed Identification in Soybean: Comparing RGB and Multispectral Sensor Performance. Journal of Agriculture and Food Research, 101784.
  10. Sunil, G. C., Khan, A., Horvath, D., & Sun, X*. (2025). Evaluation of multispectral imaging for freeze damage assessment in strawberries using AI-based computer vision technology. Smart Agricultural Technology, 10, 100851.
  11. Vullaganti, N., Ram, B. G., & Sun, X. (2025). Precision agriculture technologies for soil site-specific nutrient management: A comprehensive review. Artificial Intelligence in Agriculture. 15(2), 147-161.
  12. Ram, B. G., Howatt, K., Mettler, J., & Sun, X*. (2025). Addressing computation resource exhaustion associated with deep learning training of three-dimensional hyperspectral images using multiclass weed classification. Artificial Intelligence in Agriculture, 15(2), 131-146.
  13. Ram, B. G., Sunil, G. C., & Sun, X*. (2025). Herschel vision: A hyperspectral image processing software for data preparation in machine learning pipelines. SoftwareX, 30, 102089.
  14. Nijhum, P., Sunil, G. C., Horvath, D., & Sun, X*. (2025). Deep Learning for Plant Stress Detection: A Comprehensive Review of Technologies, Challenges, and Future Directions. Computers and Electronics in Agriculture, 229, 109734.
  15. Rai, N., Pathak, H., Mahecha, M. V., Buckmaster, D. R., Huang, Y., Overby, P., & Sun, X*. (2024). A case study on canola (Brassica napus L.) potential yield prediction using remote sensing imagery and advanced data analytics. Smart Agricultural Technology, 100698.
  16. Sunil, G. C., Upadhyay, & Sun, X*. (2024). Development of Software Interface for AI-Driven Weed Control in Robotic Vehicles, with Time-Based Evaluation in Indoor and Field Settings. Smart Agricultural Technology 100678.
  17. Sunil, G. C., Koparan, C., Upadhyay, A., Ahmed, M. R., Zhang, Y., Howatt, K., & Sun, X*. (2024). A Novel Automated Cloud-Based Image Datasets for High Throughput Phenotyping in Weed Classification. Data in Brief, 111097.
  18. Zhang, X., Feng, G., & Sun, X*. (2024). Advanced Technologies of Soil Moisture Monitoring in Precision Agriculture. Journal of Agriculture and Food Research, 101473.
  19. Mensah, B., Rai, N., Betitame, K., & Sun, X*. (2024). Advances in Weed Identification Using Hyperspectral Imaging: A Comprehensive Review of Platform Sensors and Deep Learning Techniques. Journal of Agriculture and Food Research, (2024): 101388.
  20. Upadhyay, A., Zhang, Y., Koparan, C. Rai, N., Howatt, K., Bajwa, S. G., & Sun, X*. (2024). Advances in ground robotic technologies for site-specific weed management in precision agriculture: A review. Computers and Electronics in Agriculture, 225, 109363.

Presentations

  1. 2025 ND CTE Professional Development Conference, Bismarck, ND, USA. Workshop Speaker.
  2. 2025 Elevate: An AI in Agriculture Summit, Fargo, ND, USA. Invited Speaker/Panelist
  3. 2024 ND/MN Lamb & Wool Convention, Fargo, ND, USA. Invited Speaker/Panelist
  4. 2024 UAS Summit & Expo – Grand Forks, ND, USA. Invited Speaker/Panelist
  5. 2024 NDSU Professional Development Panel – AI in Higher Education, Fargo, ND, USA. Invited Speaker/Panelist
  6. 2024 Autonomous Nation Conference, Fargo, ND, USA. Invited Speaker/Panelist
  7. 2024 National Institute of Animal Agriculture Webinar, Virtual. Invited Speaker
  8. 2024 Leadership, Education, Advocacy, and Promotion (LEAP) Conference, Fargo, ND, USA. Invited Speaker
  9. 2024 Advanced Crop Advisers Workshop, Fargo, ND, USA. Invited Speaker