Summary
Sajjad Mozaffari is a data scientist and ML researcher with nine years of experience, specializing in deep learning for vehicle trajectory prediction and automated driving systems. He holds a PhD from the University of Warwick and has authored 11+ papers while leading data-driven modules for Level 3/4 AV projects across major European consortia like Hi-Drive and L3Pilot. Proficient in PyTorch, seq2seq and Transformer models, he combines academic rigor with hands-on deployment work—building ML-assisted annotation pipelines, ROS LiDAR algorithms, and web interfaces for large vehicular databases. At WMG he directed motorway and urban driving data efforts and now contributes to industry at Featurespace, bridging research and product engineering. Notably, his research blends customised losses and multimodal transformers for trajectory prediction, demonstrating an ability to turn large-scale datasets (including Waymo) into deployable perception and planning enablers.
9 years of coding experience
6 years of employment as a software developer
Master of Science (MSc), Electrical Engineering (Control Systems), 3.58/4, Master of Science (MSc), Electrical Engineering (Control Systems), 3.58/4 at University of Tehran
Doctor of Philosophy - PhD, ENGINEERING, Doctor of Philosophy - PhD, ENGINEERING at University of Warwick