Sun, Shangpeng
Ph.D. | Assistant Professor
Smart Production Systems Engineering

Dr. Shangpeng Sun is Assistant Professor in the Department of Bioresource Engineering at the Macdonald Campus of McGill University. He obtained his second Ph.D. from the University of Georgia (USA) and the first Ph.D. from Beijing Jiaotong University (China), following undergraduate and graduate studies at Xi’an University of Science and Technology (China) and Beijing Jiaotong University. He performed postdoctoral research at the University of Georgia in 2020 before joining McGill.
Currently accepting graduate students
shangpeng.sun [at] mcgill.ca (Contact Professor Sun)
Active Affiliations
- ASABE/CSBE (American Society of Agricultural and Biological Engineers)
- ITSC-312 Machine Vision, P-127 Robotics Student Design, ASABE
- Centre SEVE
- Review Editor, Frontiers in Plant Science
- Guest Editor, Remote Sensing
B.Sc. (Xi’an University of Science and Technology)
M.Sc. (Beijing Jiaotong University)
Ph.D. (Beijing Jiaotong University)
Ph.D. (University of Georgia)
Dr. Shangpeng Sun’s main research interests are to develop and adopt innovative sensing technologies and computational methodology for solving challenges in next-generation smart agriculture, aiming to improve the production of high-quality food in the face of the rapidly growing human population and global environmental change. For example, he develops ground/aerial remote sensing platforms to gather crop data and designs data mining algorithms using artificial intelligence, 2D/3D computer vision, and statistical theory to quantify and predict plant growth and development.
Current Research Projects
High-throughput plant phenotyping: High-throughput plant phenotyping remains a bottleneck for crop breeding and functional genomics studies. Dr. Sun’s research aims to develop computational methods using 2D/3D computer vision and machine/deep learning for a quantitative description of plant phenotypic traits.
Crop growth and development monitoring: Dr. Sun develops unmanned ground/aerial vehicle platforms integrating sensors such as RGB, thermal, and multispectral cameras to monitor crops periodically, and build mathematical models for quantitative evaluation of the plant growth and development.
3D point cloud reconstruction and segmentation : Dr. Sun develops 3D remote sensing systems to reconstruct object 3D point clouds using LiDAR, ToF cameras, and stereo cameras and studies semantic/instance segmentation and object tracking in point clouds.
(co-taught with Prof. Clark)
(co-taught with Prof. Adamchuk)