Mackenzie Mathis
Bertarelli Foundation Chair Of Integrative Neuroscience
Geneva, Geneva, Switzerland
Summary
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Rockstar🎓
Top SchoolMackenzie Mathis is a neuroscientist-engineer who leads the Adaptive Motor Control Lab as Bertarelli Foundation Chair of Integrative Neuroscience at EPFL, translating deep learning into tools for studying adaptive behavior. A former Harvard Rowland Fellow with a PhD from Harvard, she co-developed the widely used open-source DeepLabCut platform for markerless pose estimation and continues to contribute to its usability and visualization. Based in Geneva, she bridges academic research and industry as CSO of Kinematik AI and advisor to neurotech startups, while serving on global policy bodies like the World Economic Forum’s Neurotechnology Council. Her work uniquely blends hands-on algorithm development, lab-based experiments on sensorimotor learning, and product-minded engineering to push neuroprosthetics and intelligent systems toward real-world impact.
8 years of coding experience
5 years of employment as a software developer
Bachelor's Degree, Science, Bachelor's Degree, Science at University of OregonDoctor of Philosophy (PhD), Doctor of Philosophy (PhD) at Harvard University
Github Skills (7)
jupyter-notebook10
deep-learning10
python10
data-visualisation9
data-visualization9
data-visualizations9
computer-vision9
Programming languages (12)
Github contributions (5)
DeepLabCut/DeepLabCut
Apr 2018 - Jan 2023
Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans
Role in this project:
Data Scientist
Data ScientistContributions:10 releases, 330 reviews, 509 commits in 4 years 10 months
Contributions summary:Mackenzie added comments, made minor cosmetic changes, and added a variable for colormap within various files, including a notebook file, suggesting a focus on improving the clarity and presentation of code and visualizations. The user's edits span code, a notebook, and documentation indicating that the user is likely contributing to the training of data and improving visualization tools. The user implemented changes to a demo notebook.
pytorchkeypoint-detectiondefinedmarkerlessdeep-learning
AdaptiveMotorControlLab/CEBRA-demos
Apr 2023 - Mar 2025
CEBRA Demo Notebooks. Please see all of them at the URL below:
Contributions:11 reviews, 27 PRs, 23 pushes in 1 year 10 months
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