معرفی
Aristeidis Sotiras, PhD serves as Assistant Professor of Radiology at Washington University School of Medicine and holds a secondary appointment as Assistant Professor of Electrical and Systems Engineering. He is affiliated with multiple research centers including the Computational Imaging Research Center, Roy and Diana Vagelos Division of Biology & Biomedical Sciences, Institute of Clinical and Translational Sciences, and Siteman Cancer Center.
Dr. Sotiras' research focuses on the intersection of medical image analysis, machine learning, and computational neuroscience. His work develops novel computational methods to extract information from imaging data and delineate patterns in large heterogeneous datasets. Key research areas include improving patient-specific diagnosis, advancing understanding of brain structure and function in health and disease, with specific applications in aging, Alzheimer's Disease, and neuropsychiatric disorders.
His recent publications demonstrate strong activity in neuroimaging analysis, particularly in Alzheimer's disease heterogeneity, cerebrospinal fluid dynamics, depression subtyping, and medical applications of machine learning. The research shows interdisciplinary collaboration across neuroscience, psychiatry, radiology, and computer science.
- BrightFocus award A2021042S
Dr. Sotiras actively mentors PhD/MSTP students, post-baccalaureate students, postdocs, residents, fellows, and undergraduate students. His research is supported by multiple funding sources including NIH R01 AG067103, BrightFocus Foundation, McDonnell Center for Systems Neuroscience, and the Big Ideas Program. He leads the Medical Imaging and Data Science (MINDS) Lab, which develops computer algorithms and machine learning techniques to understand brain development, aging, and tumor segmentation.
The MINDS Lab is currently working on several major projects including Advanced Machine Learning Algorithms to Quantify Heterogeneity in Alzheimer's Disease, Detecting and Characterizing Preclinical AD Using AI and Structural MRI, Structure-Function Interactions in Brain Correlates of Late Life Depression, and Closing the Loop on Unexpected Imaging Findings.
