Ammar Vora

Ammar Vora is a Machine Learning Engineer intern at Tenstorrent, focusing on writing open-source software for custom RISC-V AI accelerators and optimizing inference for large language models. As a member of the 3D Object Detection team at aUToronto, Ammar contributes to developing a pipeline for detecting various traffic obstacles using 3D LiDAR in ROS2. Previously, Ammar served as President and Co-Lead of the Computer Vision Subteam of the University of Toronto Robotics Association, participating in the Intelligent Ground Vehicle Competition. Additional experience includes roles at MEDCVR, aUToronto for lane detection, Fiverr as a software developer, and various student positions at the University of Toronto. Ammar is pursuing a Bachelor of Applied Science in Computer Engineering at the University of Toronto, following earlier studies in the International Baccalaureate program and high school.