Summary
Puranjit Singh is a data scientist and Ph.D. candidate specializing in precision agriculture, computer vision, and deep learning with eight years of applied experience across academia and industry. He develops real-time semantic segmentation and object-detection pipelines for field phenotyping, with work that has been deployed on edge devices like NVIDIA Jetson for in-situ weed detection. Currently a Precision Genomics Data Science Co-op at Bayer and a graduate researcher at the AgCypher Lab, he blends sensor-based high-throughput data collection with vision foundation models to advance digital agriculture. His MS thesis and internships at Corteva demonstrate a track record of translating novel ML research into practical agronomic tools. Colleagues describe him as a practitioner who moves models from UAV imagery and lab prototypes into operational, field-ready systems.
8 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Vision, Remote Sensing, Doctor of Philosophy - PhD, Computer Vision, Remote Sensing at University of Delaware
Master of Science - MS, Deep Learning, Data Science, Agriculture Engineering, Master of Science - MS, Deep Learning, Data Science, Agriculture Engineering at University of Nebraska-Lincoln
Senior Secondary level Education, Science, Senior Secondary level Education, Science at BCM Arya Model Sr. Sec. School
Bachelor of Technology, Computer Science, Bachelor of Technology, Computer Science at Guru Nanak Dev University, Amritsar
Punjabi, English