Mackenzie Mathis

Mackenzie Mathis is a Tenure Track Assistant Professor at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Brain Mind Institute in the Department of BIO. Her research focuses on systems neuroscience, animal behavior, and computer vision, with an emphasis on understanding neural circuits and computations underlying adaptive behavior through motor learning and control. She has developed mouse models of motor adaptation and pioneered quantitative approaches to behavior and neural circuits. Mathis has contributed to significant advancements in stem cell research, motor neuron development, and deep learning-based methods for animal behavior analysis. She is also involved in teaching and mentoring PhD students at EPFL.

Mackenzie Weygandt Mathis is a researcher at the Swiss Federal Institute of Technology in Lausanne (EPFL) specializing in Systems Neuroscience, Sensorimotor Control, Computer Vision, and Machine Learning. Her work focuses on developing deep learning tools for analyzing animal behavior and neural activity, with applications in neuroscience and wildlife conservation. She has pioneered methods like DeepLabCut for markerless pose estimation and introduced frameworks for multi-animal tracking and behavioral analysis. Her research bridges computational techniques with biological systems to decode neural representations and understand motor adaptation. Her publications emphasize the integration of machine learning with experimental neuroscience to advance behavioral and neural analysis.