Summary
Tim Hu is an AI engineer and visiting research fellow with 11 years of experience applying deep learning to real-world perception, time-series, and graph problems. He developed core perception algorithms at Pony.ai—leading camera-LiDAR fusion work that boosted detection in construction zones—and built edge-optimized ML systems at Landing AI and Landing’s Jetson deployment. A Stanford MS alumnus and first-author AAAI-AIES 2019 contributor, Tim blends rigorous research with production engineering across Python, C++, TensorFlow/PyTorch, CUDA and ROS. He also delivers practical business impact, having automated industry classification and analytics for a 4,000-member business association. Comfortable across autonomous driving, manufacturing inspection, and healthcare analytics, he’s equally at home optimizing training pipelines and shipping low-latency inference on constrained hardware.
11 years of coding experience
6 years of employment as a software developer
Bachelor of Engineering (BEng) Civil Engineering, Bachelor of Engineering (BEng) Civil Engineering at The University of Nottingham Ningbo China
Bachelor of Engineering (BEng) Civil and Environmental Engineering, Bachelor of Engineering (BEng) Civil and Environmental Engineering at University of Nottingham
Summer School: Physics & English as a Second Language, Summer School: Physics & English as a Second Language at University of California, Berkeley
Master of Science (M.S.) Statistics Environmental Fluid Mechanics & Hydrology, Master of Science (M.S.) Statistics Environmental Fluid Mechanics & Hydrology at Stanford University