About Me

Hi! I train & ship 3D visual perception models at Tesla. These models are at the core of many cool Tesla products, including Autopilot/FSD, High-Fidelity Park Assist, Vision Autopark, and Actually Smart Summon.

Previously, I researched computer vision & deep learning at the Statistical Visual Computing Lab for 5 years. I published several papers to CVPR/CVPRW; areas of interest include 3D reconstruction, 2D/3D detection, domain adaptation, self-supervised learning. For details, see the projects page.

I earned my Masters degree in Machine Learning and Data Science at UC San Diego. More details about my background can be found in my resume.

Highlights and News

• Awarded Tesla Exceptional Performance Equity Grant, given to top 20% talent in Autopilot [Aug 2024]
• Promoted to Senior Machine Learning & Computer Vision Engineer at Tesla [Feb 2024]
• Machine Learning & Computer Vision Engineer at Tesla [Aug 2022]
• Masters Degree in Machine Learning and Data Science at UCSD; MS thesis studies learned visual invariances using hierarchical datasets [Apr 2022]
• Published CVPRW 2022 Paper on test-time 3D shape refinement for domain robustness [Apr 2022]
• Awarded NSF Graduate Research Fellowship (NSF GRFP) from the US National Science Foundation Agency [Mar 2020]
• Awarded Sloan Graduate Fellowship from the Sloan Foundation [Sep 2019]
• Published CVPR 2019 Paper on neural network robustness [Jun 2019]

Contact

BrandnLeung@gmail.com