Mackenzie Weygandt Mathis

Prof. Mackenzie Weygandt Mathis is Tenure-Track Assistant Professor and Bertarelli Foundation Chair of Integrative Neuroscience at EPFL’s Brain Mind Institute. Leading the Mathis Lab since 2020, she unites machine learning and systems neuroscience to decipher how brains learn and control movement.

Education:

• PhD in Neuroscience, Harvard University (2017, advisor Naoshige Uchida)
• Post-doctoral training, University of Tübingen with Matthias Bethge (2017)
• Rowland Fellow, Harvard University (2017-2020)

Research Focus: the lab develops open-source AI tools (DeepLabCut, CEBRA, AmadeusGPT) and combines them with large-scale neural recordings in behaving mice to uncover the neural basis of adaptive motor control. Core themes include sensorimotor learning, proprioception, and brain-inspired algorithms for robotics.

Publications Trend: recent work spans robust machine-learning methods (ICLR, AISTATS 2025), foundational models for pose estimation (SuperAnimal, 2024), and integrative studies linking neural population dynamics to muscle-level control (Nature 2023, Cell 2024).

Scientific Awards:

• Swiss Science Prize Latsis 2024
• Robert Bing Prize 2024
• Eric Kandel Young Neuroscientist Prize 2023
• FENS EJN Young Investigator Prize 2022
• Vallee Scholar, ELLIS Scholar, NSF Graduate Fellow

Advising & Funding: she mentors 4 current PhD students and several postdocs, supported by SNSF Starting Grant (1.5 M CHF), CZI, Novartis, Radala Foundation, and Kavli Foundation grants.

Labs & Teams: the Mathis Lab is located at Campus Biotech, Geneva, and actively collaborates with the Alexander Mathis group, Allen Institute, and international consortiums on open-source neuroscience tools.