Dan Kessler

Dan Kessler is an Assistant Professor in the Department of Statistics & Operations Research (STOR) at the University of North Carolina at Chapel Hill, with a joint appointment in the School of Data Science and Society (SDSS). His research focuses on statistical analysis of networks, selective inference, high-dimensional statistics, human neuroimaging, computational neuroscience, and high-performance computing.

Before joining UNC, he completed a PhD in Statistics at the University of Michigan under Professor Liza Levina. He was an NSF Mathematical Sciences Postdoctoral Research Fellow and a PIMS-Simons/UW Data Science Fellow at the University of Washington, where he collaborated with Professor Daniela Witten.

His work bridges statistical theory and neuroimaging applications, particularly in understanding brain network dynamics and their implications for mental health conditions like ADHD and PTSD. Key contributions include developing scalable methods for connectome-based disease prediction and analyzing functional connectivity in clinical populations.

He has received notable fellowships, including the NSF-MSPRF and PIMS-Simons awards, recognizing his innovative interdisciplinary research. His studies frequently integrate multimodal data to address questions in computational neuroscience and translational medicine.