Taihong Xiao
Software Engineer at Google DeepMind
Mountain View, California, United States
Summary
🤩
Rockstar🎓
Top SchoolTaihong Xiao is a software engineer and machine learning researcher with a decade of experience bridging cutting-edge academic research and industry impact, currently working at Google DeepMind in Mountain View. He holds a PhD in Computer Science from UC Merced and has a strong publication record in computer vision, semi-supervised learning, neural architecture search, and semantic correspondence, with work appearing in ECCV, IJCV, AISTATS and others. His internships and collaborations span Google, NVIDIA, MEGVII, and NEC Labs, where he contributed novel methods (and patents) for optical flow, contrastive representation learning, and efficient image retrieval. Taihong also contributes practical ML tooling and playful projects—such as improving an AI agent for the popular WeChat Jump game—demonstrating attention to robustness and deployment details. Known for combining rigorous theory with hands-on implementation across TensorFlow and PyTorch, he thrives on turning research insights into reproducible, production-ready systems.
10 years of coding experience
8 years of employment as a software developer
Summer Program Mathematics, Summer Program Mathematics at University of California, BerkeleyMaster's degree Applied Mathematics, Master's degree Applied Mathematics at Peking UniversityBachelor's degree Mathematics, Bachelor's degree Mathematics at Shandong UniversityDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of California, Merced
English, Chinese
Github Skills (9)
computer-vision10
aiml10
python10
ai10
ml10
tensorflow9
android8
automations7
automation7
Programming languages (4)
Github contributions (5)
Prinsphield/Wechat_AutoJump
Dec 2017 - Jan 2018
AI plays WeChat Jump Game
Role in this project:
ML Engineer
ML EngineerContributions:14 commits, 7 PRs, 74 pushes in 26 days
Contributions summary:Taihong primarily worked on improving the AI's gameplay within the WeChat Jump Game project. Their contributions include removing debugging code, fixing a target position error, and rounding press times to integers for improved accuracy. Furthermore, the user addressed an error related to screenshot retrieval, enhancing the program's robustness. These changes collectively refined the AI's ability to accurately measure and jump across platforms.
jumpjump-gamewechat
Prinsphield/DNA-GAN
Nov 2017 - Apr 2018
Contributions:13 commits, 11 pushes, 1 branch in 5 months
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