Mackenzie Mathis

Mackenzie Weygandt Mathis is an American scientist, software developer, and faculty at the École Polytechnique Fédérale de Lausanne. Her research asks how the brain adapts to a changing world, aiming to uncover internal models and the mechanisms of adaptive sensorimotor behavior in intelligent systems—“adaptive intelligence”. Her lab studies adaptive processes in animals and develops new artificial intelligence (AI) methods to inform adaptive AI systems and translational research.

Early life and education Mathis conducted her undergraduate education at the University of Oregon receiving a bachelors of science in 2007. She then worked as a senior research technician and lab manager at the Project A.L.S. Laboratory for Stem Cell Research at Columbia University from 2007 to 2012. Working under the mentorship of Dr. Christopher E. Henderson and Dr. Hynek Wichterle, Mathis modelled amyotrophic lateral sclerosis (A.L.S.) using stem cell-derived motor neurons. and the other in Nature Biotechnology on benchmarking iPS stem cell lines ability to make motor neurons. Mathis then moved to Boston and joined the graduate program in molecular and cellular biology (MCB) at Harvard University. On her way to completing her PhD, she also completed a master's degree. Mathis was able to merge her interests in motor control with Uchida's expertise in neural recordings and behavioral analysis to forge a new scientific direction in the lab Near the end of her PhD Mathis was awarded the Rowland Fellowship which provided five years of funding to start her own lab at Harvard's Rowland Institute in Cambridge, MA. In her early faculty work at Harvard, Mathis focused on pioneering deep learning tools for behavioral analysis. Her lab developed DeepLabCut, a deep learning tool to track animal posture over time. This tool relies on transfer learning to optimize an ImageNet-pretrained foundation model and the feature detectors from DeeperCut, to fine-tune on a desired new dataset after sufficient training. Mathis has shown the versatility of this tool on many diverse datasets highlighting the robust design and potential for wide use in fields even beyond neuroscience.

Mathis also developed the software and patented algorithm CEBRA. CEBRA is a machine-learning method that can be used to compress time series in a way that reveals otherwise hidden structures in the variability of the data. It excels at processing behavioural and neural data recorded simultaneously, and it can decode activity from the visual cortex of the mouse brain to reconstruct a viewed video. This method has been used on a diversity of species, including humans for high-performance brain–machine interfaces.

Mathis’ research on sensorimotor control and learning focuses on how animals adapt their movements in response to changing conditions by building and updating internal models that predict the outcomes of actions. Her lab investigates how the nervous system generates and refines these predictions, and how error signals guide adaptation when predictions fail. Using large-scale neural recordings in mice combined with naturalistic, skilled behavioral tasks, she examines the neural dynamics that link movement, posture, and proprioceptive feedback. A central theme of her work is disentangling the distinct roles of sensory and motor brain areas in encoding proprioception, muscle states, and kinematics during learning and motor adaptation.

Mathis is focused on the concept of open science and as such, the deep learning tools she designed are open access such that researchers worldwide have access to the code in order to use this tool to analyze animal behaviors and joint neural-behavioral data in an unbiased way to inform a better understanding of how neural activity drives specific behaviors. Moreover, she developed the DeepLabCut AI Residency Program that hosts workshops and residents in her lab that come from underrepresented groups in computer science.

As of August 2020, Mathis moved to the Swiss Federal Institute of Technology, Lausanne, working within the Brain Mind Institute as a tenure-track Professor, and was tenured in 2026. The lab is hosted at the Campus Biotech in Geneva, Switzerland, where Mathis holds the Bertarelli Foundation Chair of Integrative Neuroscience. Bloomberg Business Week, and The Atlantic.

Awards and honors 2025: SGV Award

2024: Swiss Science Prize Latsis 2024: Robert Bing Prize 2023: Eric Kandel Young Neuroscientist Prize 2022: FENS EJN Young Investigator Prize 2020: Bertarelli Foundation Chair of Integrative Neuroscience 2019 - 2023: CZI Essential Open Source Software for Science - grant for DeepLabCut 2019 - : Ellis Society Fellow, Natural Intelligence 2017: NVIDIA GPU Grant 2013 - 2018: National Science Foundation Graduate Research Fellowship Life Sciences – Neuroscience 2014: Dr. Ernest Peralta Fund Award for Best Qualifying Exam proposal & defense, Harvard 2012 - 2013: Morris E. Zukerman Graduate Fellowship - awarded to top students in brain sciences at Harvard GSAS