Bolei Zhou
Associate Professor
Los Angeles, California, United States
Summary
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RockstarBolei Zhou is an Associate Professor and machine learning researcher based in Los Angeles with 13 years of experience building computer vision, robotics, and generative AI systems. He leads lab work at UCLA and translates research into real-world autonomy as Chief AI Scientist at Coco, tackling sidewalk autonomy with large-scale robot learning. His open-source contributions include influential PyTorch implementations—such as Temporal Relation Networks, Class Activation Mapping, and Places365 integrations—demonstrating a knack for turning research ideas into practical, reproducible code. Equally comfortable in academia and applied product settings, he blends theoretical insight with engineering rigor to push perception and embodied AI toward deployment.
13 years of coding experience
English, Chinese, German
Github Skills (21)
pytorch10
python10
image-recognition10
machine-learning10
reinforcement-learning10
mask-rcnn10
deep-learning10
faster-rcnn10
computer-vision10
image-classification9
evaluation9
trainings9
neural-network9
eval9
modeling9
Programming languages (10)
Github contributions (5)
CSAILVision/places365
May 2016 - Jul 2020
The Places365-CNNs for Scene Classification
Role in this project:
ML Engineer
ML EngineerContributions:65 commits, 4 PRs, 66 pushes in 4 years 2 months
Contributions summary:Bolei primarily focused on integrating and adapting pre-trained PyTorch models for scene classification within the Places365 dataset. Their contributions include adding PyTorch model implementations, modifying existing Python scripts for CPU support and model loading, and updating the demo script to be compatible with PyTorch 0.4. The user also worked on preparing and making available the necessary model weights for the PyTorch implementation. These changes centered around making the project accessible using the PyTorch framework.
resnetdeep-learningcnnsscene-classificationscene
ucla-rlcourse/RLexample
Feb 2019 - Oct 2020
Some basic examples of playing with RL
Role in this project:ML Engineer
ML EngineerContributions:18 commits, 1 PR, 42 pushes in 1 year 7 months
Contributions summary:Bolei primarily contributes to the development and implementation of Reinforcement Learning (RL) algorithms for the Pong game using PyTorch. Their work includes building and training policy gradient models like REINFORCE and Actor-Critic, incorporating baselines, and optimizing them for performance. The commits demonstrate the iterative process of model development, with updates and bug fixes applied to improve the training process and model performance. The user demonstrates an understanding of model saving and loading for resuming the training process.
reinforcement-learningplayingmachine-learningstable-baselines
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