Daniel Rowe

Dr. Daniel Rowe is a Professor of Data Science and Co-Director in the Department of Mathematical and Statistical Sciences at Marquette University. His research focuses on Bayesian statistics, computational neuroscience, and medical imaging, particularly in fMRI analysis. He has contributed extensively to improving fMRI signal processing techniques, including Bayesian approaches for brain activity mapping and parallel imaging reconstruction methods like GRAPPA and SENSE.

His work emphasizes statistical methodologies to address challenges in neuroimaging, such as noise reduction, artifact correction, and the development of complex-valued analysis frameworks. Notable contributions include the Bayesian merged utilization of GRAPPA and SENSE (BMUGS) for enhanced fMRI detection and efficient fully Bayesian approaches for brain activity mapping.

Dr. Rowe collaborates on interdisciplinary projects, including cardiac chamber modeling using Bayesian neural networks and studies on radiation-induced cardiotoxicity. His publications span high-impact journals like the Annals of Applied Statistics, Magnetic Resonance Imaging, and the Journal of the Royal Statistical Society.