Summary
Zongyang Li is a Senior Computational Scientist with nine years of hands-on experience designing and implementing image and video processing algorithms, now based in Missouri. He combines deep expertise in C++ and Python with a decade-long focus on object detection, segmentation, deep embedding networks, and 3D point cloud analysis for large-scale phenotyping and surveillance applications. At the Donald Danforth Plant Science Center he led explainable AI and sensor-fusion work—building deep metric learning pipelines to match thermal and RGB scenes and embedding cultivar-specific trait signatures for visualization and analysis. His background includes productionizing Faster-RCNN and SegNet models for 2D/3D data, GAN-based color correction, and optimized video reconnaissance systems from earlier industry roles. Comfortable across the full lifecycle from research to integration, he excels at scaling complex pipelines to handle gigapixel imagery and volumetric sensor data. He brings a rare mix of academic rigor and field-proven engineering pragmatism, translating biological and remote-sensing needs into deployable, interpretable ML solutions.
9 years of coding experience
4 years of employment as a software developer
Bachelor’s Degree, Computer Science, Bachelor’s Degree, Computer Science at Huazhong University of Science and Technology
Master’s Degree, Computer Science, Master’s Degree, Computer Science at Guilin University of Electronic Technology
Chinese, English