Mu Zhou
Switzerland, China
Summary
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SeniorMu Z is a researcher with eight years of experience at the intersection of computer vision and machine learning, currently based in the Zürich area and working at Zoo Zürich. Trained with a PhD in Neuroscience from EPFL and an MS in Computer Science from University of Tsukuba, Mu focuses on few-shot learning, domain adaptation, and pose estimation, bringing both theoretical rigor and applied experience from internships and research roles including SonyAI and AIST. Their background blends neuroscience-informed perspectives with hands-on systems research, enabling work that tackles data-scarce and cross-domain perception problems. Notably, Mu transitioned from student researcher roles into a doctoral assistantship at EPFL and later into industry-facing research, demonstrating an aptitude for moving ideas from lab prototypes toward real-world applications.
9 years of coding experience
Github Skills (33)
toolbox10
metric-learning10
few-shot-learning10
meta-learning9
pose-estimation9
android-application8
deep-learning8
denoising8
autoencoder8
android-app7
generative-adversarial-network7
rxkotlin7
computer-vision7
image-manipulation6
kotlin-android6
Programming languages (3)
Github contributions (5)
zhoumu53/few_shot_learning
Aug 2018 - Jan 2019
Awesome papers in few-shot learning/one-shot learning.
Contributions:41 commits, 34 pushes, 1 branch in 5 months
few-shot-learningone-shot-learningmeta-learningzero-shot-learningmetric-learning
zhoumu53/DeepLabCut
Jul 2021 - Jan 2026
Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals
Contributions:9 pushes, 5 branches in 4 years 7 months
pytorchdefinedmarkerlessdeep-learningpose-estimation
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