Anne Draelos, Ph.D.

Assistant Professor, Biomedical Engineering

Primary Website

Draelos Lab


  • Ph.D., Physics, Duke University
  • M.S., Electrical & Computer Engineering, Duke University
  • B.S., Physics, North Carolina State University
  • B.S., Computer Science, North Carolina State University

Additional Title(s)

  • Assistant Professor, Computational Medicine & Bioinformatics
  • Member, Michigan Neuroscience Institute

Personal Pronouns



  • Biomede 241: Statistics, Computation, & Data Analysis


Dr. Draelos studied Physics and Computer Science as an undergraduate at NC State University, followed by an ECE master’s and Ph.D. in Physics at Duke University. She then cross-trained and completed a postdoctoral fellowship in systems neuroscience at Duke University, studying how to build algorithms for real-time analysis of neural data.

As a faculty at UM, her research focuses on machine learning and statistical techniques to facilitate real-time analysis of high-dimensional neural and behavioral data. The Draelos lab aims to understand computation in large-scale neural circuits through adaptive perturbations and real-time inference in behaving animals. They develop statistical machine-learning algorithms capable of altering experimental conditions based on real-time analysis of neural and behavioral data and work closely with a number of experimental collaborators.


  • 2024 Sloan Fellow in Neuroscience, Sloan Foundation
  • Career Award at the Scientific Interface, Burroughs Wellcome Fund
  • Research Scouts Award, UM Medical School Office of Research
  • Career Award at the Scientific Interface from the Burroughs Wellcome Fund