Incoming M.Eng. Student · CAU
B.Eng. Graduate · HUC
Hello! I am Daoze Tang, an incoming Master's student in Computer Science and Technology at China Agricultural University, where I will be supervised by Prof. Xiang Li.
My research spans Computer Science broadly, centering on Computer Vision—and Object Detection in particular—where I build efficient algorithms and robust visual recognition systems.
Beyond my own research, I founded and lead a student research group that mentors motivated peers and fields teams for academic competitions.
Outside the lab, I draw inspiration from the arts: I play guitar and read widely across literary genres.
Of course, I am far from perfect, and I know I cannot please everyone—something I try to take in stride, learning from honest feedback as I go.
I am actively seeking academic collaborations, joint doctoral training programs, and Ph.D. opportunities. If my work resonates with you, I would be glad to hear from you.
Scientific Reports · 2025
This research presents a scalable object detection framework adaptable to various application scenarios and contributes a novel design paradigm for efficient deep learning-based object detection.
PLOS One · 2024
This work proposes an improved, lightweight algorithm, LCFF-Net, designed to enhance the extraction of tiny target features and optimize the use of computational resources, and presents different scale versions of the LCFF-Net algorithm to suit various deployment environments.
