Qiyang Li

Qiyang Li is an accomplished part-time researcher at the Vector Institute since October 2016, focusing on advancements in Lipschitz-constrained convolutional networks and high-fidelity waveform reconstruction for music data. Additionally, Qiyang serves as the Road and Lane Detection Team Lead at aUToronto while previously interning at NVIDIA, where notable projects included physics-based animation with deep reinforcement learning and enhancing AI robotics through the NVIDIA Isaac SDK. As a co-founder and Vice President Academics of the University of Toronto Machine Intelligent Student Team, Qiyang promoted awareness in the field of machine intelligence and contributed to real-time road segmentation projects. Early in academic pursuits, Qiyang gained research experience at the University of Toronto Institute of Aerospace Studies, improving quadrotor trajectory tracking through deep learning techniques. Qiyang holds a Bachelor of Applied Science in Engineering Science from the University of Toronto, earned in 2020.