Ziteng Ji is a fourth-year UC Berkeley student majoring in Computer Science and Applied Mathematics with nine years of hands-on experience in robotics, reinforcement learning, and computer vision research. Currently an undergraduate researcher at Berkeley AI Research focusing on hybrid robotics and humanoid RL, he has contributed to DARrell Group projects and held research roles at Tsinghua and CMU's Robotics Institute in search-based planning. Based in the San Francisco Bay Area, he blends strong theoretical foundations with applied systems work—shipping experiments across simulation and hardware—and is active in UC Berkeley’s CS honor society. Notably, his profile reflects a pattern of short, intensive research engagements across top labs, signaling an ability to rapidly prototype and iterate on complex robotics problems.
9 years of coding experience
1 year of employment as a software developer
Bachelor's degree, Computer Science & Applied Mathematics, Bachelor's degree, Computer Science & Applied Mathematics at University of California, Berkeley
High School Diploma, High School Diploma at IMG Academy
A super light-weight deep learning library based on NumPy in PyTorch fashion.
Contributions:33 commits, 1 PR, 21 pushes in 3 years 1 month
pytorchlight-weightlightdeep-learningnumpy
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