Dr. Anne Draelos first studied physics and computer science as an undergraduate at North Carolina State University. She completed a masters in electrical & computer engineering and a PhD in physics at Duke University, focused on the interplay between various quantum phenomena in networked systems. She then cross-trained as a postdoctoral fellow in neuroscience to study arguably the most complex network around: the brain. 

Now at U-M BME as faculty, her lab is focused on machine learning and statistical techniques to facilitate real-time analysis of high-dimensional neural and behavioral data. Dr. Draelos currently holds a Career Award at the Scientific Interface from the Burroughs Wellcome Fund.

Her lab aims to understand computation in large-scale neural circuits through adaptive perturbations and real-time inference in behaving animals. We develop statistical machine learning algorithms capable of altering experimental conditions based on real-time analysis of neural and behavioral data.